What to do with future Ambiguity Error about overlapping names when sorting?

xref https://github.com/pandas-dev/pandas/pull/17361

In [24]: df = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([1, 2], name='a'))

In [25]: df.sort_values(['a', 'b'])
/Users/taugspurger/.virtualenvs/pandas-dev/bin/ipython:1: FutureWarning: 'a' is both an index level and a column label.
Defaulting to column, but this will raise an ambiguity error in a future version
  #!/Users/taugspurger/Envs/pandas-dev/bin/python3
Out[25]:
   a  b
a
1  1  3
2  2  4

What should the user do in this situation? Should we provide a keyword to disambiguate? A literal like pd.ColumnLabel('a') or pd.IndexName('a')? Or do we require that they rename an index or column? Right now, they’re essentially stuck with the last one. If we want to discourage that, then I suppose that’s OK. But it’s somewhat common to end up with overlapping names, from e.g. a groupby.

cc @jmmease

[TomAugspurger]

To be clear, I’m OK with going down this road of “indexes are a special type of column, so don’t have overlapping names”. Perhaps we’ll use this issue to collect use-cases where they arise, and document how to avoid them?

e.g. the last one would be something like “use groupby('a', as_index=False)”.

[xieyuheng]

It is not ambiguous when I specify axis=0.

df = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([1, 2], name='a'))

df.sort_values(['a', 'b'], axis=0)

But the warning still.