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  • calculate percentiles · 3 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
140419634 https://github.com/pydata/xarray/issues/561#issuecomment-140419634 https://api.github.com/repos/pydata/xarray/issues/561 MDEyOklzc3VlQ29tbWVudDE0MDQxOTYzNA== mathause 10194086 2015-09-15T14:54:53Z 2015-09-15T14:54:53Z MEMBER

Thanks

 
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   calculate percentiles 105442957
138743009 https://github.com/pydata/xarray/issues/561#issuecomment-138743009 https://api.github.com/repos/pydata/xarray/issues/561 MDEyOklzc3VlQ29tbWVudDEzODc0MzAwOQ== shoyer 1217238 2015-09-09T01:00:49Z 2015-09-09T01:00:49Z MEMBER

Adding a dedicated method for calculating percentiles/quantiles would also be a good idea: https://github.com/xray/xray/issues/303

 
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   calculate percentiles 105442957
138729068 https://github.com/pydata/xarray/issues/561#issuecomment-138729068 https://api.github.com/repos/pydata/xarray/issues/561 MDEyOklzc3VlQ29tbWVudDEzODcyOTA2OA== clarkfitzg 5356122 2015-09-08T23:18:43Z 2015-09-08T23:18:43Z MEMBER

ds = xray.tutorial.load_dataset('air_temperature') percents = ds.groupby('time.month').reduce(np.percentile, q=5)

Producing:

In [80]: percents Out[80]: <xray.Dataset> Dimensions: (month: 12) Coordinates: * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12 Data variables: air (month) float64 239.7 239.3 244.3 251.7 261.4 271.5 274.0 272.5 ...

 
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   calculate percentiles 105442957

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