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/5030#issuecomment-1058532014,https://api.github.com/repos/pydata/xarray/issues/5030,1058532014,IC_kwDOAMm_X84_F-qu,2448579,2022-03-03T21:56:55Z,2022-03-03T21:57:21Z,MEMBER,"My concern is that we could conceivably adding `missing_dims` to any function that takes a `dim` argument, which is pretty much the whole API. 

For datatree, you could apply the reduction with the set-intersection of provided dims and dims present in a node (if that's the right term).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,830638672
https://github.com/pydata/xarray/issues/5030#issuecomment-797850555,https://api.github.com/repos/pydata/xarray/issues/5030,797850555,MDEyOklzc3VlQ29tbWVudDc5Nzg1MDU1NQ==,2448579,2021-03-13T02:23:38Z,2021-03-13T02:23:38Z,MEMBER,"Alternatively, you could run the following at the beginning

``` python
# not sure if syntax is right
model_datasets = [
    ds.expand_dims('member_id') 
    if ""member_id"" not in ds.coords else ds 
    for ds in model_datasets
]
```

so all your datasets are consistent.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,830638672