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/1234#issuecomment-751222858,https://api.github.com/repos/pydata/xarray/issues/1234,751222858,MDEyOklzc3VlQ29tbWVudDc1MTIyMjg1OA==,26384082,2020-12-25T09:49:51Z,2020-12-25T09:49:51Z,NONE,"In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity

If this issue remains relevant, please comment here or remove the `stale` label; otherwise it will be marked as closed automatically
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,203630267
https://github.com/pydata/xarray/issues/1234#issuecomment-457209817,https://api.github.com/repos/pydata/xarray/issues/1234,457209817,MDEyOklzc3VlQ29tbWVudDQ1NzIwOTgxNw==,5635139,2019-01-24T14:11:12Z,2019-01-24T15:38:36Z,MEMBER,"> Alternatively, we might simply skip variables in Dataset.where if they don't have overlapping dimensions. The logic gets a good deal more complex, though. Currently where is a thin wrapper around np.where.

Would skipping variables without the dimension be preferable? Or do people expect the broadcast?

We recently had a discussion re skipping variables that don't have the dimension supplied using `.reduce`, although that was for a clearer example, where broadcasting would be less relevant - e.g. rolling along a dimension","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,203630267
https://github.com/pydata/xarray/issues/1234#issuecomment-457121127,https://api.github.com/repos/pydata/xarray/issues/1234,457121127,MDEyOklzc3VlQ29tbWVudDQ1NzEyMTEyNw==,500246,2019-01-24T09:08:42Z,2019-01-24T09:08:42Z,CONTRIBUTOR,Maybe this just needs a note in the documentation then?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,203630267
https://github.com/pydata/xarray/issues/1234#issuecomment-457074615,https://api.github.com/repos/pydata/xarray/issues/1234,457074615,MDEyOklzc3VlQ29tbWVudDQ1NzA3NDYxNQ==,26384082,2019-01-24T05:45:51Z,2019-01-24T05:45:51Z,NONE,"In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity
If this issue remains relevant, please comment here; otherwise it will be marked as closed automatically
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,203630267
https://github.com/pydata/xarray/issues/1234#issuecomment-275721597,https://api.github.com/repos/pydata/xarray/issues/1234,275721597,MDEyOklzc3VlQ29tbWVudDI3NTcyMTU5Nw==,1217238,2017-01-27T17:23:03Z,2017-01-27T17:23:03Z,MEMBER,"You're not the first person to be confused about this (see https://github.com/pydata/xarray/issues/1217). This is indeed working as expected, though maybe not in the most useful way.

`where` works by broadcasting its arguments, and when `ds.c` (along the `a` dimension) gets broadcasted with `ds.y` (along the `b` dimension), the result gets the union of both dimensions.

Alternatively, we might simply skip variables in Dataset.where if they don't have overlapping dimensions. The logic gets a good deal more complex, though. Currently `where` is a thin wrapper around `np.where`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,203630267