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/3291#issuecomment-823833533,https://api.github.com/repos/pydata/xarray/issues/3291,823833533,MDEyOklzc3VlQ29tbWVudDgyMzgzMzUzMw==,3924836,2021-04-21T07:12:11Z,2021-04-21T07:13:45Z,MEMBER,"Just wanted to rekindle discussion here and ping @dcherian and @benbovy , the current workaround for pandas DatetimeIndex with timezone info (dtype='datetime64[ns, EST]') is to drop the timezone piece or use `to_index()` and operate in pandas, then reassign the time coordinate: See https://github.com/pydata/xarray/issues/1036 and https://github.com/pydata/xarray/issues/3163. 

If I'm following https://github.com/pydata/xarray/blob/master/design_notes/flexible_indexes_notes.md this is another potential example of improved user-friendliness where we could have timezone-aware indexes and therefore call pandas methods like `pandas.core.indexes.datetimes.DatetimeIndex.tz_convert()` directly as a DataArray method? 

This would definitely be great for remote sensing data that is usually stored with UTC timestamps, but often analysis requires converting to local time.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,490618213