[REVIEW] Raise error when numeric_only=True for non-numeric Series

[galipremsagar]

Description

This PR raises an error when numeric_only=True for rank if the Series is of non-numeric dtype.

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[galipremsagar]

rank related pytests:

(cudfdev) pgali@dt07:/nvme/0/pgali/cudf$ pytest python/cudf/cudf/tests/test_rank.py -n 4
/nvme/0/pgali/envs/cudfdev/lib/python3.10/site-packages/pytest_benchmark/logger.py:46: PytestBenchmarkWarning: Benchmarks are automatically disabled because xdist plugin is active.Benchmarks cannot be performed reliably in a parallelized environment.
  warner(PytestBenchmarkWarning(text))
============================================================================================= test session starts ==============================================================================================
platform linux -- Python 3.10.9, pytest-7.2.1, pluggy-1.0.0
benchmark: 4.0.0 (defaults: timer=time.perf_counter disable_gc=False min_rounds=5 min_time=0.000005 max_time=1.0 calibration_precision=10 warmup=False warmup_iterations=100000)
rootdir: /nvme/0/pgali/cudf/python/cudf/cudf/tests, configfile: pytest.ini
plugins: anyio-3.6.2, benchmark-4.0.0, xdist-3.2.0, cov-4.0.0, hypothesis-6.68.2, cases-3.6.13
gw0 [501] / gw1 [501] / gw2 [501] / gw3 [501]
........................................................................................................................................................................................................ [ 39%]
......................................................................................................................................................................................................... [ 79%]
....................................................................................................                                                                                                     [100%]
============================================================================================= 501 passed in 5.78s ==============================================================================================


(cudfdev) pgali@dt07:/nvme/0/pgali/cudf$ conda list | grep "pandas"
pandas                    2.0.0rc0                 pypi_0    pypi