build(deps): bump pandas from 2.3.2 to 3.0.0

[dependabot]

Bumps pandas from 2.3.2 to 3.0.0.

Release notes

Sourced from pandas's releases.

pandas 3.0.0

We are pleased to announce the release of pandas 3.0.0, a major release from the pandas 2.x series. This release includes various new features, bug fixes, and performance improvements, as well as possible breaking changes.

The pandas 3.0 release removed a functionality that was deprecated in previous releases. It is recommended to first upgrade to pandas 2.3 and to ensure your code is working without warnings, before upgrading to pandas 3.0.

Highlights include:

• Dedicated string data type by default
• Consistent copy/view behaviour with Copy-on-Write (CoW) (a.k.a. getting rid of the SettingWithCopyWarning)
• New default resolution for datetime-like data
• Initial support for the new pd.col syntax

See the announcement blog post and the detailed release notes for a list of all the changes.

Pandas 3.0.0 supports Python 3.11 and higher. The release can be installed from PyPI

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Pandas 3.0.0rc2

No release notes provided.

Pandas 3.0.0rc1

No release notes provided.

Pandas 3.0.0rc0

We are pleased to announce a first release candidate for pandas 3.0.0. If all goes well, we'll release pandas 3.0.0 in a few weeks.

See the [whatsnew][0] for a list of all the changes.

The release is available on conda-forge and PyPI.

The release can be installed from PyPI

python -m pip install --upgrade --pre pandas==3.0.0rc0

Or from conda-forge

conda install -c conda-forge/label/pandas_rc pandas==3.0.0rc0

Please report any issues with the release candidate on the pandas issue tracker.

... (truncated)

Commits

• 366ccdf RLS: 3.0.0
• 139f4d0 DOC: split/reorder other enhancements section in 3.0.0 whatsnew notes (#63762)
• fd2a4f4 TST: assert reading of legacy pickles against current data (#61792)
• cc0bcaa DOC: update whatsnew section on datetimelike resolution (#63780)
• 3ddbb49 DOC: remove 2.3.4 whatsnew file from released 3.0 docs (#63779)
• ee63532 CLN: Create temporary HDF5 file path and HDFStore for pytables tests (#63492)
• 9512e99 CoW: better chained assignment warning message for update() method (#63500)
• 1db90d5 API: rename read_iceberg selected_fields keyword to columns (#63748)
• c9b51fa BUG: .str methods failing on PyArrow using regex with \Z (#63705)
• 7cff0f4 API: Period.to_timestamp default to microsecond unit (#63760)
• Additional commits viewable in compare view

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[jirhiker]

1. String dtype behavior change can subtly affect CSV cleaning logic

• pandas 3.0 changes default string handling; you normalize owner keys with string ops in /Users/jross/Programming/DIG/OcotilloAPI/transfers/contact_transfer.py:131.
• This area is the highest behavior-risk zone (null handling + .astype(str) + .replace({"": pd.NA})).

2. Copy-on-Write default in 3.0 may change mutation assumptions

• Your code mostly uses reassignment (good), but you do many filtered-frame workflows (for example /Users/jross/Programming/DIG/OcotilloAPI/transfers/util.py:435).
• I did not find obvious chained-assignment patterns, so this looks low risk, but still worth regression testing transfer paths.

What I did not find as a likely blocker:

• No usage of classic removed/deprecated APIs like DataFrame.append, .ix, iteritems, date_parser=, etc.

Sources: pandas 3.0.0 release notes, pandas 3.0 string migration guide.