issues: 104484316

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
104484316 MDU6SXNzdWUxMDQ0ODQzMTY= 557 CDO-like convenience methods to select times 6883049 open 0     9 2015-09-02T13:42:48Z 2022-04-18T16:03:35Z   CONTRIBUTOR      

I feel like the time selecting features of xray can be improved. Currently, some common operations are too involved or verbose, like selecting the data in a group of months that are not a standard season (e.g. the monsoon season in india JJAS), or in non consecutive years (e.g. El Niño years). I think it would be great to implement (and easy), some methods inspired in the widely used Climate Data Operators https://code.zmaw.de/projects/cdo For example: selyear, selmon, selday and selhour.

Then we could easily do a composite of JJAS seasons in El Niño years like this:

pr_dataset = xray.open(my_precipitation_dataset) elnino_years = [year list here...] pr_dataset.selyear(elnino_years).selmon([6, 7, 8, 9]).mean('time')

This would make me very happy. The way to go would be to write methods that call grouby, then select the years/months, merge them, and return the corresponding dataset/dataarray, but I am not sure about what is the most efficient way to do this.

 
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