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  • shoyer · 2 ✖

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  • aggregation functions treat duck arrays differently depending on dtype · 2 ✖

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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
527253633 https://github.com/pydata/xarray/issues/3241#issuecomment-527253633 https://api.github.com/repos/pydata/xarray/issues/3241 MDEyOklzc3VlQ29tbWVudDUyNzI1MzYzMw== shoyer 1217238 2019-09-02T22:46:14Z 2019-09-02T22:46:14Z MEMBER

Can you try merging in the latest version of xarray master into your branch? I think this issue was fixed just recently by https://github.com/pydata/xarray/pull/3254. When I test this myself, both versions seem to do the right thing: ``` In [5]: xr.DataArray(data=np.arange(10).astype(float) * ureg.m).median() Out[5]: <xarray.DataArray ()> <Quantity(4.5, 'meter')>

In [6]: xr.DataArray(data=np.arange(10).astype(int) * ureg.m).median() Out[6]: <xarray.DataArray ()> <Quantity(4.5, 'meter')> ```

 
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   aggregation functions treat duck arrays differently depending on dtype 484097190
527250978 https://github.com/pydata/xarray/issues/3241#issuecomment-527250978 https://api.github.com/repos/pydata/xarray/issues/3241 MDEyOklzc3VlQ29tbWVudDUyNzI1MDk3OA== shoyer 1217238 2019-09-02T22:15:47Z 2019-09-02T22:15:47Z MEMBER

@keewis could you clarify that example? Both those examples appear to be the same code, with different results!

 
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   aggregation functions treat duck arrays differently depending on dtype 484097190

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