GH-41039: [Python] ListView pandas tests should use np.nan instead of None

[danepitkin]

Rationale for this change

ListView pandas conversion tests are failing in upstream development branches of pandas/numpy.

What changes are included in this PR?

• Use np.nan instead of None when comparing with an expected Pandas Series.

Are these changes tested?

Yes, unit tests updated.

Are there any user-facing changes?

No.

• GitHub Issue: [Python] ListView pandas conversion tests are failing when comparing None vs np.nan #41039

[danepitkin]

@github-actions crossbow submit -g python

[github-actions]

⚠️ GitHub issue #41039 has been automatically assigned in GitHub to PR creator.

[github-actions]

Revision: 6c1be46

Submitted crossbow builds: ursacomputing/crossbow @ actions-88b36e596b

Task	Status
example-python-minimal-build-fedora-conda
example-python-minimal-build-ubuntu-venv
test-conda-python-3.10
test-conda-python-3.10-cython2
test-conda-python-3.10-hdfs-2.9.2
test-conda-python-3.10-hdfs-3.2.1
test-conda-python-3.10-pandas-latest
test-conda-python-3.10-pandas-nightly
test-conda-python-3.10-spark-v3.5.0
test-conda-python-3.10-substrait
test-conda-python-3.11
test-conda-python-3.11-dask-latest
test-conda-python-3.11-dask-upstream_devel
test-conda-python-3.11-hypothesis
test-conda-python-3.11-pandas-upstream_devel
test-conda-python-3.11-spark-master
test-conda-python-3.12
test-conda-python-3.8
test-conda-python-3.8-pandas-1.0
test-conda-python-3.8-spark-v3.5.0
test-conda-python-3.9
test-conda-python-3.9-pandas-latest
test-cuda-python
test-debian-12-python-3-amd64
test-debian-12-python-3-i386
test-fedora-39-python-3
test-ubuntu-20.04-python-3
test-ubuntu-22.04-python-3

[AlenkaF]

LGTM +1.

Opened an issue for the failing build connected to #40976: #41043

[conbench-apache-arrow]

After merging your PR, Conbench analyzed the 7 benchmarking runs that have been run so far on merge-commit bf3c1b9.

There was 1 benchmark result indicating a performance regression:

• Commit Run on ursa-i9-9960x at 2024-04-05 20:03:10Z
  • tpch (R) with engine=arrow, format=parquet, language=R, memory_map=False, query_id=TPCH-15, scale_factor=1

The full Conbench report has more details. It also includes information about 3 possible false positives for unstable benchmarks that are known to sometimes produce them.