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/5727#issuecomment-904597086,https://api.github.com/repos/pydata/xarray/issues/5727,904597086,IC_kwDOAMm_X8416w5e,5802846,2021-08-24T12:28:18Z,2021-08-24T12:31:21Z,CONTRIBUTOR,"Thank you! You are right. I guess based on the docs for [Assigning values with indexing](http://xarray.pydata.org/en/stable/user-guide/indexing.html#assigning-values-with-indexing) I assumed only `.loc` features item assignment .  I vaguely remember there where issues with assigning via integer-based indexing. Well, propably my bad.

Should we add an example how to perform masking this way to the docs? There are many examples about masking using different ways, but not this simple, intuitive way.

Even now, it's not really clear to me why ""boolean""-masking should only work with integer-indexing and not label-indexing. Given that the highlighted `maybe_cast_to_coords_dtype` is the only reason it does not work for label-based indexing. 

edit: probably the reason is to support label-based indexing for boolean coords?!","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,976207971
https://github.com/pydata/xarray/issues/3608#issuecomment-888250482,https://api.github.com/repos/pydata/xarray/issues/3608,888250482,IC_kwDOAMm_X8408aBy,5802846,2021-07-28T11:58:28Z,2021-07-28T11:58:28Z,CONTRIBUTOR,"You are right. It's quite confusing. I've already added a `stride` parameter in my PR #3607 
I didn't follow through with it and at the moment the checks are not successful anymore.
Maybe someone else could give an opinion on the pro/cons of a `stride` parameter in rolling? ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,535703663
https://github.com/pydata/xarray/issues/3608#issuecomment-851469496,https://api.github.com/repos/pydata/xarray/issues/3608,851469496,MDEyOklzc3VlQ29tbWVudDg1MTQ2OTQ5Ng==,5802846,2021-05-31T12:50:37Z,2021-05-31T12:50:37Z,CONTRIBUTOR,"Quickly glancing over `sliding_window_view` I didn't immediately understand how to use it with stride. Would I need to 
1. transform the DataArray to dask array using chunk (which may involve an overhead!?), 
2. then use rolling which itself uses `sliding_window_view` because its a dask array!? 
3. Then use `isel` with stride on the new dimension?

> `reduce` can easily support `stride` by passing it on here:

I think that's what I did in #3607. It's been a while","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,535703663
https://github.com/pydata/xarray/issues/5290#issuecomment-839758891,https://api.github.com/repos/pydata/xarray/issues/5290,839758891,MDEyOklzc3VlQ29tbWVudDgzOTc1ODg5MQ==,5802846,2021-05-12T13:08:51Z,2021-05-12T20:28:10Z,CONTRIBUTOR,"Thanks a lot! Very helpful comments. I'll check out your PR.

If i understand it correct, zarr does some autochunking while saving coordinates even without setting specific encodings, at least for bigger coordinate arrays.
I can get what I want by creating a zarr store with compute=False then deleting everything except the metadata manually on the filesystem level. Then each call to_zarr() with region results in only one coordinate chunk being created on disk.
Reading with xr.open_zarr() works as expected: the coordinate contains nan except for the region written before.
The (potentially very large) coordinate still needs to fit in memory though... either when creating the dummy zarr store (which could be done differently) or when opening it. Is that correct? That wont work for my use case when the coordinate is very large.

Do you know an alternative? Would it help if I store the coordinate with a non-dimension name? i guess it all boils down to the way xarray recreates the Dataset from zarr store. The only way I can think of right know to make useful ""chunked indices""  are some form of hierachical indexing. Each chunk is represented by the first index in that chunk. Which would probably only work for sequential indices. I dont know if such indexing exists for pandas. Maybe a hierachical chunking could be useful for some very large datasets!? I dont know if that would create too much overhead but it would be a structured way to access long-term high-res data. In a way I think thats what I'm trying to implement. I would be happy about any pointers to existing solutions.


Regarding the documentation: I could provide an example with a time coordinate, which would illustrate two issues I encountered.
* region requires index space coordinates (I know: it's already explained in the docs... :)
* the before mentioned ""coordinates need to be predefined"" issue.

(Sorry if this bug report is not the right place to ask all these questions)

 
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,887711474
https://github.com/pydata/xarray/pull/3610#issuecomment-573060295,https://api.github.com/repos/pydata/xarray/issues/3610,573060295,MDEyOklzc3VlQ29tbWVudDU3MzA2MDI5NQ==,5802846,2020-01-10T14:38:03Z,2020-01-10T14:38:03Z,CONTRIBUTOR,"Okay, this looks better. Thanks for the help! I had to try it again myself, because you cherry-picked some commits I accidentally merged into this branch (non-related to this fix).
Could you check if this is good now?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,536214141
https://github.com/pydata/xarray/pull/3610#issuecomment-573021208,https://api.github.com/repos/pydata/xarray/issues/3610,573021208,MDEyOklzc3VlQ29tbWVudDU3MzAyMTIwOA==,5802846,2020-01-10T12:44:05Z,2020-01-10T12:44:05Z,CONTRIBUTOR,"I don't mind, thanks :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,536214141
https://github.com/pydata/xarray/pull/3610#issuecomment-573019892,https://api.github.com/repos/pydata/xarray/issues/3610,573019892,MDEyOklzc3VlQ29tbWVudDU3MzAxOTg5Mg==,5802846,2020-01-10T12:39:58Z,2020-01-10T12:39:58Z,CONTRIBUTOR,I tried to merge with master yesterday and did it again today. There might be a problem with the way I tried to fix the `whats-new.rst` issues. It might be faster if I open a new pull request and re-insert the changes!?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,536214141
https://github.com/pydata/xarray/issues/3608#issuecomment-564023352,https://api.github.com/repos/pydata/xarray/issues/3608,564023352,MDEyOklzc3VlQ29tbWVudDU2NDAyMzM1Mg==,5802846,2019-12-10T13:05:10Z,2019-12-10T13:05:10Z,CONTRIBUTOR,"
> Previous enhancement requests asking for a `stride` argument to `rolling`: https://github.com/pandas-dev/pandas/issues/15354, https://github.com/pandas-dev/pandas/issues/22976, https://github.com/pandas-dev/pandas/issues/27654#issue-474416717, https://github.com/dask/dask/issues/4659, https://github.com/numpy/numpy/issues/7753

_Originally posted by @pilkibun in https://github.com/pandas-dev/pandas/issues/26959#issuecomment-511233955_","{""total_count"": 4, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 3}",,535703663