Fix BoxPlot KeyError when columns is not provided

[cachafla]

Pull Request Description

What and why?

validmind.plots.BoxPlot raised a KeyError whenever it was run without an explicit columns parameter:

KeyError: "None of [Index([None], dtype='object')] are in the [columns]"

_validate_inputs wrapped the default columns=None into [None] and indexed the dataframe with it before the if columns is None branch could run, so that branch was dead code. Because BoxPlot is tagged data_quality, this broke any loop over vm.tests.list_tests(tags=["data_quality"], ...), which is exactly what notebooks/use_cases/validation/validate_application_scorecard.ipynb does (reported by Hannes on the JupyterHub demo environment; the traceback pointed at BoxPlot._validate_inputs, not at the preprocess/feature-engineering cells).

The fix defaults to dataset.feature_columns_numeric, the same approach HistogramPlot, ViolinPlot and CorrelationHeatmap already use, and filters explicit columns against that list instead of indexing the frame directly (so a misspelled column is skipped rather than raising).

How to test

• uv run python -m unittest tests.unit_tests.plots.test_BoxPlot (new; two of the four cases fail on main).
• Run the for test in dq: loop in validate_application_scorecard.ipynb. All 11 data_quality tests, including validmind.plots.BoxPlot, now pass on the preprocessed lending club dataset.

What needs special review?

Explicit columns are now filtered to numeric feature columns, so passing the target column explicitly no longer plots it. This matches the sibling plot tests.

Dependencies, breaking changes, and deployment notes

None.

Release notes

Fixed validmind.plots.BoxPlot raising a KeyError when run without the columns parameter, which also broke running all data_quality tests in a loop.

Checklist

• What and why
• Screenshots or videos (Frontend)
• How to test
• What needs special review
• Dependencies, breaking changes, and deployment notes
• Labels applied
• PR linked to Shortcut
• Unit tests added (Backend)
• Tested locally
• Documentation updated (if required)
• Environment variable additions/changes documented (if required)

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