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- aggregation functions treat duck arrays differently depending on dtype · 2 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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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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