Should Dataset enforce some ordering of dims in its variables?

[max-sixty]

I'm not sure on this one. I'm currently having a bunch of issues with this sort of Dataset:
(notice the dims are (d, c) and (c, d) for different variables)

<xray.Dataset>
Dimensions:               (c: 193, d: 6781)
Coordinates:
  * d                   (d) object 5218 5219 5220 5221 5222 5223 5224 ...
  * c                (c) object LDS. ...
    j                    (c, d) bool False False False False ...
Data variables:
    r                  (d, c) float64 nan -0.05083 nan ...
    s                  (d, c) float64 nan -0.05083 nan ...
    n                  (c, d) float64 nan nan nan nan nan ...

In my case, this is particularly painful when passing the result of ds.r.to_pandas() into a function expecting a DataFrame with a certain orientation when that orientation isn't reliable.

Is this a problem generally?

If it is, I could imagine a few solutions - enforce ordering, offer a method on a DataSet to align the dims, offer a kwarg on .to_pandas() to allow specifying the dims-axis mapping, etc

[shoyer]

The easiest way to enforce that dimensions have a consistent order is to use the transpose method, e.g., ds.transpose('c', 'd'). Does that suffice? I'm not sure enforcing an ordering would be a good idea -- it makes the xray data model slightly less flexible.

[max-sixty]

Great, I didn't know transpose could do that, cheers.
FWIW this doesn't seem to enforce the ordering of the dims of coords in a DataArray - let me know if you want me to open an issue / post an example.

I think that makes sense re enforcing the ordering. I think my current use case is very specific (applying functions to pandas objects, which don't recognize dims, and so fail if things are in the wrong order). More generally, I'd hope functions would be robust to the order of dimensions.

I'll close for now.

Thanks as ever!