tree 070a30f6f6ae2073ae968ba7beb0b2cf4374bc41
parent a15adeb3a215ad2ef7222e18112d23cdffa8569a
author sai <saidatt@Saidatts-MBP.attlocal.net> 1715129056 +0900
committer Hyukjin Kwon <gurwls223@apache.org> 1715129056 +0900

[SPARK-48045][PYTHON] Pandas API groupby with multi-agg-relabel ignores as_index=False

### What changes were proposed in this pull request?
In a Scenario where we use GroupBy in PySpark API with relabeling of aggregate columns and using as_index = False,
the columns with which we group by are not returned in the DataFrame. The change proposes to fix this bug.

Example:
ps.DataFrame({"a": [0, 0], "b": [0, 1]}).groupby("a", as_index=False).agg(b_max=("b", "max"))

Result:
_  b_max
0      1

Required Result:
_  a  b_max
0  0      1

### Why are the changes needed?
The relabeling part of the code only uses only the aggregate columns. In a scenario where as_index=True, it is not an issue as the columns with which we group by are included in the index. When as_index=False, we need to append the columns with which we grouped by to the relabeling code.

Please, check the commits/PR for the code changes

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
- Passed GA
- Passed Build tests
- Unit Tested including scenarios in addition to the one provided in the Jira ticket

### Was this patch authored or co-authored using generative AI tooling?
No

Closes #46391 from sinaiamonkar-sai/SPARK-48045-2.

Authored-by: sai <saidatt@Saidatts-MBP.attlocal.net>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>