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/3332#issuecomment-705098106,https://api.github.com/repos/pydata/xarray/issues/3332,705098106,MDEyOklzc3VlQ29tbWVudDcwNTA5ODEwNg==,1217238,2020-10-07T17:54:32Z,2020-10-07T17:54:32Z,MEMBER,"The loop via slicing is not a terrible option. The trick construct() uses with views only really makes sense with NumPy arrays, not with dask.

There are also true streaming moving window algorithms that work very well for computing various statistics (e.g., mean and variance). These are implemented in bottleneck (e.g., `move_mean`) and could be wrapped in xarray if desired for methods like `rolling(...).mean()`. These aren't implemented in dask yet, though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,496809167
https://github.com/pydata/xarray/issues/3332#issuecomment-534709955,https://api.github.com/repos/pydata/xarray/issues/3332,534709955,MDEyOklzc3VlQ29tbWVudDUzNDcwOTk1NQ==,1217238,2019-09-24T19:21:22Z,2019-09-24T19:21:22Z,MEMBER,"It uses a view for allocating the initial result, but I think applying boundary conditions means that we end up doing a copy.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,496809167