issue_comments: 94084387

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https://github.com/pydata/xarray/issues/393#issuecomment-94084387 https://api.github.com/repos/pydata/xarray/issues/393 94084387 MDEyOklzc3VlQ29tbWVudDk0MDg0Mzg3 1217238 2015-04-17T21:57:46Z 2015-04-19T00:00:56Z MEMBER

I would probably write a custom utility function to make the appropriate boolean vector. Something like:

python def in_jjas(xray_obj): months = [6, 7, 8, 9] month_vec = xray_obj['time.month'] result = reduce(np.logical_or, [month_vec == m for m in months]) return result.rename('in_jjas')

Then you can use it like the following:

``` In [3]: ds = xray.Dataset({'time': pd.date_range('2000-01-01', periods=365)})

In [9]: in_jjas(ds) Out[9]: <xray.DataArray 'in_jjas' (time: 365)> array([False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], dtype=bool) Coordinates: * time (time) datetime64[ns] 2000-01-01 2000-01-02 2000-01-03 2000-01-04 2000-01-05 ...

In [11]: ds.sel(time=in_jjas(ds)) Out[11]: <xray.Dataset> Dimensions: (time: 122) Coordinates: * time (time) datetime64[ns] 2000-06-01 2000-06-02 2000-06-03 2000-06-04 2000-06-05 ... Data variables: empty ```

 
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