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/5075#issuecomment-832793635,https://api.github.com/repos/pydata/xarray/issues/5075,832793635,MDEyOklzc3VlQ29tbWVudDgzMjc5MzYzNQ==,5567953,2021-05-05T15:40:30Z,2021-05-05T15:40:30Z,NONE,"A ""close enough"" option can take care of issues such as in `xarray.where`  in situations where the coordinates are very close but not exactly matched ([here](https://stackoverflow.com/questions/67376150/multidimensional-xarray-where-dorps-coordinates)) (e.g. due to Geotif roudning, [here ](https://github.com/corteva/rioxarray/discussions/332)) . ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/4213#issuecomment-656392705,https://api.github.com/repos/pydata/xarray/issues/4213,656392705,MDEyOklzc3VlQ29tbWVudDY1NjM5MjcwNQ==,5567953,2020-07-09T23:05:19Z,2020-07-09T23:05:19Z,NONE,"Thanks. The problem is I don't really know where the common coordinates are. However, since I know the extent of each tile, with some preprocessing I should be able to find/trim them. 

On the side note. It would be great if mosaicing dataset with common coordinate was added to the xarray (like mosacing rasters). What really happened was I had a large area, then I used xarray to clip it into smaller tiles to make calculations more feasible. After I did the calculations on tiles and decided to stitch them together this problem raised.  Your approach would solve this issue, but having it as part of xarray definitely helps many geospatial applications where, for many reasons, we deal with tiles of data with common coordinates. 
Thanks again. 
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,654150730
https://github.com/pydata/xarray/issues/4213#issuecomment-656383386,https://api.github.com/repos/pydata/xarray/issues/4213,656383386,MDEyOklzc3VlQ29tbWVudDY1NjM4MzM4Ng==,5567953,2020-07-09T22:34:47Z,2020-07-09T22:34:47Z,NONE,"Thanks @TomNicholas for a thorough explanation. Now it makes sense. I thought this is a process like mosaicing rasters using rasterio.merge. Yes, it would be great if you can add an example on how to find and trim overlapping coordinates. I don't really know how to find common coordinates in spatial datasets using isel. 

Thanks
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