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/3763#issuecomment-583869461,https://api.github.com/repos/pydata/xarray/issues/3763,583869461,MDEyOklzc3VlQ29tbWVudDU4Mzg2OTQ2MQ==,19554926,2020-02-09T17:12:54Z,2020-02-09T17:12:54Z,NONE,"Hi all, thanks for the reply. Just to clarify, I'm making the suggestion that any one (or more) of these categorical interpolation techniques be incorporated into the internals of xarray so that any categorical arrays present in the dataset (properly aligned to a given dimension, of course) are interpolated automatically. As it stands, resampling such ""mixed"" datasets requires manually partitioning the numerical arrays from the categorical arrays and handling their interpolation separately. What makes xarray so appealing to me is how much of the laborious, error-prone, and not-so-extensible coding I've had to do in order to maintain relationships between various objects. It just seems to me like there is an opportunity here to push more into the background.

Forgive me if I'm mistaken or if this view is naive or possibly just a bad idea. I've only been working with xarray for a couple of days. Thanks again.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,562075354