Add pandas 3 compatibility for string dtype handling

[guillaume-vignal]

Fixes #714

This PR updates several string-related checks to align with pandas 3, where text columns are inferred as str instead of object by default.

Some parts of the codebase still assume text data uses the object dtype. Under pandas 3, this can lead to missed categorical columns, incorrect type classification, or rejected string postprocessing.

This change targets pandas 3 behavior. Pandas 2 compatibility is still supported

[Copilot]

Pull request overview

This PR aims to make Shapash compatible with pandas 3’s default string dtype inference by updating string/categorical dtype checks across core utilities, examples, and tests, and by bumping the minimum supported pandas version.

Changes:

• Update string/categorical column detection logic in utilities and example code to account for pandas 3 string inference.
• Adjust unit tests’ expected preprocessing metadata (data_type) to reflect string dtype handling changes.
• Bump pandas minimum version to >=2.3.0 in pyproject.toml.

Reviewed changes

Copilot reviewed 11 out of 11 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
tutorial/production_and_ops/tuto-prod03-batch-scoring-parquet.ipynb	Updates dtype-based selection before Parquet write to cast text-like columns.
tests/unit_tests/utils/test_transform.py	Updates expected data_type values in preprocessing-mapping related tests.
tests/unit_tests/utils/test_columntransformer_backend.py	Updates expected data_type values in CT inverse/transform tests.
tests/unit_tests/utils/test_check.py	Updates expected data_type values in preprocessing consistency tests.
tests/unit_tests/utils/test_category_encoders_backend.py	Updates expected data_type values in category-encoder backend tests.
tests/unit_tests/explainer/test_smart_predictor.py	Updates expected data_type values used in preprocessing checks.
tests/unit_tests/decomposition/test_inverse_contribution.py	Updates expected data_type values used in inverse contribution tests.
shapash/webapp/webapp_launch_DVF.py	Updates example categorical feature detection for encoding.
shapash/utils/transform.py	Updates categorical missing-value handling selection logic.
shapash/utils/clustering.py	Updates categorical detection for color encoding in clustering/plots.
pyproject.toml	Raises minimum pandas version to >=2.3.0.

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Copilot reviewed 11 out of 11 changed files in this pull request and generated 3 comments.

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Copilot reviewed 40 out of 40 changed files in this pull request and generated 9 comments.

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Copilot reviewed 40 out of 40 changed files in this pull request and generated 6 comments.

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Copilot reviewed 40 out of 40 changed files in this pull request and generated 2 comments.

Comments suppressed due to low confidence (1)

shapash/utils/check.py:421

• In the regex branch, the DataFrame-type error message incorrectly mentions the upper/lower method, which can mislead users when diagnosing invalid postprocessing configuration.

                    if not pd.api.types.is_string_dtype(x[key]):
                        raise ValueError(f"Expected string object to modify with upper/lower method in {key} dict")

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Pull request overview

Copilot reviewed 40 out of 40 changed files in this pull request and generated 3 comments.

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Pull request overview

Copilot reviewed 40 out of 40 changed files in this pull request and generated 3 comments.

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Copilot reviewed 40 out of 40 changed files in this pull request and generated 1 comment.

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Copilot reviewed 41 out of 41 changed files in this pull request and generated 1 comment.

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Copilot reviewed 41 out of 41 changed files in this pull request and generated 2 comments.

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Copilot reviewed 43 out of 43 changed files in this pull request and generated 2 comments.

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Copilot reviewed 37 out of 37 changed files in this pull request and generated 4 comments.