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  • groupby beahaviour w.r.t. non principal coordinates · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
747391520 https://github.com/pydata/xarray/issues/2148#issuecomment-747391520 https://api.github.com/repos/pydata/xarray/issues/2148 MDEyOklzc3VlQ29tbWVudDc0NzM5MTUyMA== aurghs 35919497 2020-12-17T11:47:44Z 2020-12-17T11:47:44Z COLLABORATOR

I think this has been fixed at some point. it can be closed.

 
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   groupby beahaviour w.r.t. non principal coordinates 324032926
540187230 https://github.com/pydata/xarray/issues/2148#issuecomment-540187230 https://api.github.com/repos/pydata/xarray/issues/2148 MDEyOklzc3VlQ29tbWVudDU0MDE4NzIzMA== dcherian 2448579 2019-10-09T20:45:58Z 2019-10-09T20:45:58Z MEMBER

Everything but this last example works as expected

``` arr = xr.DataArray( np.ones((5, 2)), dims=('x', 'y'), coords={ 'x': ('x', np.array([1, 1, 1, 2, 2])), 'x1': ('x', np.array([1, 1, 1, 2, 2])), 'x2': ('x', np.array([1, 2, 3, 4, 5])), } )

arr.groupby(xr.DataArray([1,1,1,2,2], dims=('x'), name='y')).mean('x')

<xarray.DataArray (y: 4)> array([1., 1., 1., 1.]) Coordinates: * y (y) int64 1 2

```

 
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   groupby beahaviour w.r.t. non principal coordinates 324032926
389935163 https://github.com/pydata/xarray/issues/2148#issuecomment-389935163 https://api.github.com/repos/pydata/xarray/issues/2148 MDEyOklzc3VlQ29tbWVudDM4OTkzNTE2Mw== aurghs 35919497 2018-05-17T16:52:16Z 2018-05-17T17:27:07Z COLLABORATOR

The coordinates are grouped correctly: ```python list(arr.groupby('x'))

[(1, <xarray.DataArray (x: 3)> array([1., 1., 1.]) Coordinates: * x (x) int64 1 1 1 x2 (x) int64 1 2 3), (2, <xarray.DataArray (x: 2)> array([1., 1.]) Coordinates: * x (x) int64 2 2 x2 (x) int64 4 5)] ``` I think the grouping make sense. But once the groups are collapsed with some operation, I'm not sure that can be found a corresponding meaningful operation to apply to the grouped coordinates.

In the following cases the mean after gourpby() works as expected:

``` arr = xr.DataArray( np.ones(5), dims=('x',), coords={ 'x': ('x', np.array([1, 1, 1, 2, 2])), 'x1': ('x', np.array([1, 1, 1, 2, 2])), 'x2': ('x', np.array([1, 2, 3, 4, 5])),

}

)

arr.groupby('x1').mean('x')

<xarray.DataArray (x1: 2)> array([1., 1.]) Coordinates: * x1 (x1) int64 1 2

arr.groupby((xr.DataArray([1,1,1,2,2], dims=('x'), name='x3'))).mean('x')

<xarray.DataArray (x3: 2)> array([1., 1.]) Coordinates: * x3 (x3) int64 1 2 Also also if I try to group with an array named with as the dimension along which we perform the mean, I get the same problem:python arr.groupby(xr.DataArray([1,1,1,2,2], dims=('x'), name='x')).mean('x')

<xarray.DataArray (x: 2)> array([1., 1.]) Coordinates: * x (x) int64 1 2 x1 (x) int64 1 1 1 2 2 x2 (x) int64 1 2 3 4 5 ```

If I try to use an other dimension name we obtain again an strange behaviour: ```python arr = xr.DataArray( np.ones((5, 2)), dims=('x', 'y'), coords={ 'x': ('x', np.array([1, 1, 1, 2, 2])), 'x1': ('x', np.array([1, 1, 1, 2, 2])), 'x2': ('x', np.array([1, 2, 3, 4, 5])), } )

arr.groupby(xr.DataArray([1,1,1,2,2], dims=('x'), name='y')).mean('x')

<xarray.DataArray (y: 4)> array([1., 1., 1., 1.]) Coordinates: * y (y) int64 1 2

``` In this case probably it should raise an error. 

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   groupby beahaviour w.r.t. non principal coordinates 324032926
389885906 https://github.com/pydata/xarray/issues/2148#issuecomment-389885906 https://api.github.com/repos/pydata/xarray/issues/2148 MDEyOklzc3VlQ29tbWVudDM4OTg4NTkwNg== fmaussion 10050469 2018-05-17T14:27:19Z 2018-05-17T14:27:19Z MEMBER

Yes, definitely looks like a bug. I wonder if aggregating the non-dimension coordinate would lead to meaningful results in some cases, but I guess that in most cases it wouldn't. 

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   groupby beahaviour w.r.t. non principal coordinates 324032926

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