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  • darothen · 3 ✖

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  • GroupBy like API for resample · 3 ✖

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  • NONE · 3 ✖
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280104546 https://github.com/pydata/xarray/issues/1269#issuecomment-280104546 https://api.github.com/repos/pydata/xarray/issues/1269 MDEyOklzc3VlQ29tbWVudDI4MDEwNDU0Ng== darothen 4992424 2017-02-15T18:59:17Z 2017-02-15T18:59:17Z NONE

@MaximilianR Oh, the interface is easy enough to do, even maintaining backwards-compatibility (already have that working). I was considering going the route done with GroupBy and the classes that compose it, like DatasetGroupBy... basically, we just record the wanted resampling dimension and inject the grouping/resampling operations we want. Also adds the ability to specialize methods like .first() and .last(), which is done under the current implementation.

But.... if there's a simpler way, that might be preferable!

 
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   GroupBy like API for resample 207587161
279845588 https://github.com/pydata/xarray/issues/1269#issuecomment-279845588 https://api.github.com/repos/pydata/xarray/issues/1269 MDEyOklzc3VlQ29tbWVudDI3OTg0NTU4OA== darothen 4992424 2017-02-14T21:44:11Z 2017-02-14T21:44:11Z NONE

Assuming we want to stick with pd.TimeGrouper under the hood, the only sticking point I've come across so far is how to have the resulting Data{Array,set}GroupBy object "remember" the resampling dimension, e.g. if you have multi-dimensional data and want to compute time means you have to call

python ds.resample(time='24H').mean('time')

or else mean will operate across all dimensions. Any thoughts, @shoyer?

 
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   GroupBy like API for resample 207587161
279810604 https://github.com/pydata/xarray/issues/1269#issuecomment-279810604 https://api.github.com/repos/pydata/xarray/issues/1269 MDEyOklzc3VlQ29tbWVudDI3OTgxMDYwNA== darothen 4992424 2017-02-14T19:32:01Z 2017-02-14T19:32:01Z NONE

Let me dig into this a bit right now. My analysis project for this afternoon was already going to require digging into pandas' resampling in more depth anyways.

 
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   GroupBy like API for resample 207587161

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