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/2363#issuecomment-412659630,https://api.github.com/repos/pydata/xarray/issues/2363,412659630,MDEyOklzc3VlQ29tbWVudDQxMjY1OTYzMA==,1217238,2018-08-13T20:51:14Z,2018-08-13T20:51:14Z,MEMBER,"This does seem to be a little inconsistent currently.

My original reasoning for the default groupby behavior was that that this felt more consistent with the behavior for non-grouped reductions, which reduces across all dimensions.

But it's probably less useful, and results in a lot of redundant code. I can only think of a few times when I've actually wanted this behavior, rather than summing over only the grouped dimension. Especially when going from 1D -> ND, this is a likely source of errors.

So instead, we could change this to:
```
ds.groupby('time.month').mean()  # result dims : ('month', 'x')
ds.groupby('time.month').mean(dim=None)  # result dims : ('month',)
```

Or maybe we could add a special constant `xarray.ALL_DIMS` to indicate all dimensions? This is probably the most readable version:
```
ds.groupby('time.month').mean(dim=xarray.ALL_DIMS)  # result dims : ('month',)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,349857086