tadeja commented on PR #48969: URL: https://github.com/apache/arrow/pull/48969#issuecomment-3804829670
@AlenkaF this is ready for final review. - Generated doc pages: [pyarrow.Table page](https://s3.amazonaws.com/arrow-data/pr_docs/48969/python/generated/pyarrow.Table.html) and [pyarrow.RecordBatch](https://s3.amazonaws.com/arrow-data/pr_docs/48969/python/generated/pyarrow.RecordBatch.html) - Both Sphinx jobs ran and completed doctests with success; [AMD64 Conda Python 3.12 Sphinx Documentation pandas 3.0.0 pypi_0 pypi ================== 385 passed, 2 skipped, 1 warning in 6.24s ===================](https://github.com/apache/arrow/actions/runs/21371826114/job/61518064753?pr=48969#step:6:2706) and [AMD64 Conda Python 3.10 Sphinx & Numpydoc pandas 2.3.3 pypi_0 pypi ======================== 385 passed, 2 skipped in 5.63s ========================](https://github.com/apache/arrow/actions/runs/21371826077/job/61589312410?pr=48969#step:6:550) - The two trivial cases where pandas 2.3.3 output expects `None` but pandas 3.0.0 expects `NaN` ` 1 4 None 2022.0` ` 1 4 NaN 2022.0` get best resolved by populating pa.array with a string instead: [first case](https://github.com/apache/arrow/pull/48969/changes#diff-cede36e8e2e0eb6e6e1ee21745db9687174527f463520c6e6d8b9e8f957bf304R3572) and [second case](https://github.com/apache/arrow/pull/48969/changes#diff-cede36e8e2e0eb6e6e1ee21745db9687174527f463520c6e6d8b9e8f957bf304R4922). - Note that I additionally removed pandas and replaced with pyarrow table for these three examples: [def itercolumns](https://github.com/apache/arrow/pull/48969/changes#diff-cede36e8e2e0eb6e6e1ee21745db9687174527f463520c6e6d8b9e8f957bf304R2068), [def remove_column](https://github.com/apache/arrow/pull/48969/changes#diff-cede36e8e2e0eb6e6e1ee21745db9687174527f463520c6e6d8b9e8f957bf304R5405) and [def join](https://github.com/apache/arrow/pull/48969/changes#diff-cede36e8e2e0eb6e6e1ee21745db9687174527f463520c6e6d8b9e8f957bf304R5659) (although these are currently not causing failures as there isn't `string` vs. `large_string` in their output). But there are more unnecessary pandas examples remaining that could be simplified in the future (`num_columns`, `num_rows` etc). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
