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/6026#issuecomment-1011446127,https://api.github.com/repos/pydata/xarray/issues/6026,1011446127,IC_kwDOAMm_X848SXFv,42455466,2022-01-12T20:58:53Z,2022-01-12T20:58:53Z,NONE,Thanks @spencerkclark! Updating to cftime version 1.5.1 fixes the issue.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1063046540
https://github.com/pydata/xarray/issues/6084#issuecomment-1011430150,https://api.github.com/repos/pydata/xarray/issues/6084,1011430150,IC_kwDOAMm_X848STMG,42455466,2022-01-12T20:35:44Z,2022-01-12T20:35:44Z,NONE,"Thanks @shoyer. I understand the need for the schema, but is there a need to actually generate the dask graph when all the user wants to do is initialise an empty zarr store? E.g., I *think* skipping [this line](https://github.com/pydata/xarray/blob/6a29380008dcd790f9adfbc290affcb767c913b2/xarray/backends/api.py#L1439) would save some of the users in my original post a lot of time.

Regardless, your suggestion to just create a low-overhead version of the array being initialised is probably better/cleaner than adding a specific option or method. Would it be worth adding the `xarray.zeros_like(ds)` recommendation to the [docs](https://xarray.pydata.org/en/stable/user-guide/io.html#appending-to-existing-zarr-stores)?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1083621690
https://github.com/pydata/xarray/issues/4610#issuecomment-852836671,https://api.github.com/repos/pydata/xarray/issues/4610,852836671,MDEyOklzc3VlQ29tbWVudDg1MjgzNjY3MQ==,42455466,2021-06-02T08:12:06Z,2021-06-02T08:12:06Z,NONE,"We have a very thin wrapper of xhistogram in xskillscore for calculating histograms from Datasets. It simply calculates the histograms independently for all variables that exist in all Datasets. This makes sense in the context of calculating skill score where the first Dataset corresponds to observations and the second to forecasts, and we want to calculate the histograms between matched variables in each dataset. However, this might be quite a specific use case and is probably not what we'd want to do in the general case. I like @TomNicholas 's proposal for Dataset functionality.

Is this what you're getting at @aaronspring ? Or am I misunderstanding?","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,750985364
https://github.com/pydata/xarray/issues/4833#issuecomment-763897041,https://api.github.com/repos/pydata/xarray/issues/4833,763897041,MDEyOklzc3VlQ29tbWVudDc2Mzg5NzA0MQ==,42455466,2021-01-20T20:00:23Z,2021-01-20T20:00:23Z,NONE,"> May be a duplicate of #4240

Yup - my apologies, I didn't find this. I'll move any further comments I have over there.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,789755611