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  • CDO-like convenience methods to select times · 6 ✖

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427335183 https://github.com/pydata/xarray/issues/557#issuecomment-427335183 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDQyNzMzNTE4Mw== shoyer 1217238 2018-10-05T11:33:45Z 2018-10-05T11:33:45Z MEMBER

dataset.time.dt.year.isin(elnino_years) should work already with.

 
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   CDO-like convenience methods to select times 104484316
427279439 https://github.com/pydata/xarray/issues/557#issuecomment-427279439 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDQyNzI3OTQzOQ== shoyer 1217238 2018-10-05T07:59:47Z 2018-10-05T08:00:28Z MEMBER

I don’t think there’s an easy way to this with vectorized indexing, but if we supported multidimensional indexing with boolean keys as proposed in https://github.com/pydata/xarray/issues/1887 (equivalent to where with drop=True) we could write pr_dataset[pr_dataset['time.year'].isin(elnino_years)]

 
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   CDO-like convenience methods to select times 104484316
427078606 https://github.com/pydata/xarray/issues/557#issuecomment-427078606 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDQyNzA3ODYwNg== rabernat 1197350 2018-10-04T16:12:43Z 2018-10-04T16:12:43Z MEMBER

Is there a way to do this easily now with vectorized indexing?

 
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   CDO-like convenience methods to select times 104484316
137257727 https://github.com/pydata/xarray/issues/557#issuecomment-137257727 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDEzNzI1NzcyNw== jhamman 2443309 2015-09-02T21:57:54Z 2015-09-02T21:57:54Z MEMBER

I'd also like to see this come into being.

My two cents on the syntax is that your second idea is best:

Python pr_dataset.sel('time.year', elnino_years)

I don't care much for option 3 since the variable name is being used as an attribute (what if my time variable is called "Times"?).

 
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   CDO-like convenience methods to select times 104484316
137182504 https://github.com/pydata/xarray/issues/557#issuecomment-137182504 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDEzNzE4MjUwNA== shoyer 1217238 2015-09-02T17:37:56Z 2015-09-02T17:37:56Z MEMBER

Currently, the way to do this is to create a boolean indexer, with something like the following:

pr_dataset.sel(time=np.in1d(pr_dataset['time.year'], elnino_years))

I agree that this is overly verbose and we can come up with something better. I'm not quite happy with selyear, though: - It's ambiguous which datetime variable the year refers do (there can be more than one time variable on some datasets). - I'm also not a big fan of adding a bunch of new API methods that are datetime specific -- it creates a lot of noise (pandas has an issue with this).

Something like pr_dataset.sel(year=elnino_years) would be the ideal fix for this second concern (we've discussed this in another issue, can't remember which one now), but it's still ambiguous which time variable it refers to.

So, some other possible ways to spell this: 1. pr_dataset.sel('time', year=elnino_years) 2. pr_dataset.sel('time.year', elnino_years) 3. pr_dataset.sel.time.year(elnino_years)

 
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   CDO-like convenience methods to select times 104484316
137134794 https://github.com/pydata/xarray/issues/557#issuecomment-137134794 https://api.github.com/repos/pydata/xarray/issues/557 MDEyOklzc3VlQ29tbWVudDEzNzEzNDc5NA== clarkfitzg 5356122 2015-09-02T15:32:17Z 2015-09-02T15:32:17Z MEMBER

Just curious- how would we currently do this?

 
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   CDO-like convenience methods to select times 104484316

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