jorisvandenbossche opened a new issue, #46179:
URL: https://github.com/apache/arrow/issues/46179
### Describe the bug, including details regarding any error messages,
version, and platform.
The pandas -> arrow conversion adds a `__inex_level_i__` column if the
dataframe has an unnamed it wants to preserve (i.e. if it is not just a pandas
RangeIndex). But if your dataframe already has such a column, you end up with a
duplicate field:
```
In [40]: df = pd.DataFrame({"col": [1, 2, 3], "__index_level_0__": [1, 2,
3]}, index=[2, 3, 4])
In [41]: df
Out[41]:
col __index_level_0__
2 1 1
3 2 2
4 3 3
In [42]: pa.table(df)
Out[42]:
pyarrow.Table
col: int64
__index_level_0__: int64
__index_level_0__: int64
----
col: [[1,2,3]]
__index_level_0__: [[1,2,3]]
__index_level_0__: [[2,3,4]]
```
We could have it bump the integer number in the generated column? (although
we would have to check how that works in the full roundtrip then)
### Component(s)
Python
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