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/1270#issuecomment-392682701,https://api.github.com/repos/pydata/xarray/issues/1270,392682701,MDEyOklzc3VlQ29tbWVudDM5MjY4MjcwMQ==,7933853,2018-05-29T07:41:53Z,2018-05-29T07:41:53Z,NONE,"thanks for your elaborate response @spencerkclark 

>Do you happen to be using a PeriodIndex because of pandas Timestamp-limitations? 

Yes, the main limitation being the limited range of years (~584) whereas my dataset spans 1800 years. Note that in glaciology, which deals with ice sheet responses over multiple millennia, this is considered a short period.

I elaborated a bit more on my problem in [this issue](https://github.com/kuchaale/X-regression/issues/6#issuecomment-390396061) which is in a unofficial repo, I realized too late.

Anyway, your code using cftime solves my problem 😄  indeed resampling to `'AS-JUN'` is what I was looking for. Still, it would be nice to have better support for PeriodIndex in the future. It has costed me a lot of time figuring out what's going on and learning the details of all the different date & time implementations. Which is a waste in the end. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207862981
https://github.com/pydata/xarray/issues/1270#issuecomment-390892554,https://api.github.com/repos/pydata/xarray/issues/1270,390892554,MDEyOklzc3VlQ29tbWVudDM5MDg5MjU1NA==,7933853,2018-05-22T07:36:40Z,2018-05-22T07:36:40Z,NONE,+1 to this issue. I'm struggling big time with an 1800-year climate model dataset that I need to resample in order to make different annual means (June-May).,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,207862981