issue_comments: 389935163
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html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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https://github.com/pydata/xarray/issues/2148#issuecomment-389935163 | https://api.github.com/repos/pydata/xarray/issues/2148 | 389935163 | MDEyOklzc3VlQ29tbWVudDM4OTkzNTE2Mw== | 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
<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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