manhha2502 opened a new pull request, #56284:
URL: https://github.com/apache/spark/pull/56284
### What changes were proposed in this pull request?
This PR adds support for `DataFrame.xs` with `axis=1` / `axis="columns"` in
pandas API on Spark.
It supports selecting cross-sections from columns, including single-level
columns, MultiIndex columns, and level-based selection by level number or level
name.
### Why are the changes needed?
`DataFrame.xs` currently supports index-axis selection, but column-axis
selection raises `NotImplementedError`.
This improves compatibility with pandas and addresses SPARK-46158.
### Does this PR introduce _any_ user-facing change?
Yes.
Previously, `DataFrame.xs(..., axis=1)` raised `NotImplementedError`.
After this change, users can select column cross-sections, for example:
~~~python
psdf.xs("metrics", axis=1)
psdf.xs("metrics", axis="columns")
psdf.xs("num_legs", axis=1, level="feature")
~~~
### How was this patch tested?
Added positive and negative test cases in `FrameIndexingMixin.test_xs`
covering `axis=1`, `axis="columns"`, MultiIndex columns, level-based selection,
missing column keys, and invalid column levels.
Also ran:
~~~bash
python -m py_compile python/pyspark/pandas/frame.py
python/pyspark/pandas/tests/indexes/test_indexing.py
git diff --check
~~~
I attempted to run the targeted unittest locally, but the source checkout
has not built Spark jars yet.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: OpenAI Codex (GPT-5)
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