issue_comments: 823833533

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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.

 
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