issue_comments: 253683651

@benbovy This is actually a good use case for no dimension labels. E.g., from my working branch:

``` In [7]: da = xr.DataArray(z, dims=('x', 'y'), name='z')

In [8]: dz_dx_xarray = da[1:, :] - da[:-1, :]

In [9]: dz_dx dz_dx_numpy dz_dx_xarray

In [9]: dz_dx_xarray Out[9]: <xarray.DataArray 'z' (x: 4, y: 5)> array([[ 0.15224392, -0.03428312, -0.10936435, 0.06149288, -0.69317859], [-0.61928605, 0.71636887, -0.05578677, -0.39489466, 0.63472963], [ 0.05180684, -0.72471438, 0.64259117, 0.24830877, -0.24006862], [ 0.44981358, 0.19054462, -0.69880118, -0.20120161, 0.08580928]])

In [10]: da.diff('x') Out[10]: <xarray.DataArray 'z' (x: 4, y: 5)> array([[ 0.15224392, -0.03428312, -0.10936435, 0.06149288, -0.69317859], [-0.61928605, 0.71636887, -0.05578677, -0.39489466, 0.63472963], [ 0.05180684, -0.72471438, 0.64259117, 0.24830877, -0.24006862], [ 0.44981358, 0.19054462, -0.69880118, -0.20120161, 0.08580928]]) ```

This does depend on the details of how .diff is implemented though. It does a loop over variables.items() instead of explicitly accessing variables corresponding to dimensions.

e.g., array.coords['x'] would return a DataArray with values range(n) (importantly, this would not change the original array). That sounds a bit weird to me (I'm not sure to understand, actually). What are the reasons/benefits of returning a DataArray instead of raising a KeyError?

The (theoretical) benefit would be an easier transition, because previously ds[dim] always worked.

As I'm working through porting xarray's test suite, I'm realizing that this may not be the best approach. If a user is relying on ds[dim] or array.coords[dim] always working, they are probably not going to be happy with inadvertently adding new coordinates like range(n) (which implies new alignment semantics). It might be a better idea to force a hard transition.

Either way, the functionality in your reset_index() PR is going to be really essential, because these range(n) indexes are going to show up inadvertently sometimes, such as converting pandas objects or .unstack().