Thanks for the thoughtful reply @benbovy

(This is a level down and you can make a decision later, so fine if you prefer to push the discussion.)

How would we handle creating xarray objects from pandas objects where they have a multiindex?

To what extent do you think this is this the "standard case" and we could default to it?

python idx = xr.PandasMultiIndex(pd_idx, "x") indexes = {"x": idx, "foo": idx, "bar": idx}

I realize there's a lot here and I've been out of this thread for a bit, so please forgive any naive questions!

I would suggest depreciating this behavior in favor of a more explicit (although more verbose) way to pass an existing pandas multi-index:

What's the rationale for deprecating this? I think my experience with users of xarray is mostly those coming from pandas; for them interop is quite important. If there's a canonical way of transforming the index, it would be friendlier to do that automatically.

```python import pandas as pd import xarray as xr

pd_idx = pd.MultiIndex.from_product([["a", "b"], [1, 2]], names=("foo", "bar")) idx = pd_idx

ds = xr.Dataset(coords={"x": idx}) ```

i.e.

``` ds = xr.Dataset(coords=coords)

ValueError: missing index(es) for coordinate(s): 'x', 'foo', 'bar'

or

create unindexed coordinates 'foo' and 'bar' and a 'x' coordinate with a single pandas index

```

I would have expected the later, both for coords=coords and for coords=pd_idx (again, with the disclaimer that I may be missing crucial parts of the puzzle here).

Should we silently reorder the coordinates and/or indexes when the levels are not passed in the right order? It seems odd requiring mapping elements be passed in a given order.

👍