Category-encoders

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* fixed: Future Warning in Pandas
* fixed: np.NaNs in numpy 2.x
* improved: performance of the hashing encoder (about twice as fast)
* deprecate the `max_sample`` parameter, it has no use anymore
* add `process_creation_method` parameter
* use concurrent.futures.ProcessPoolExecutor instead of hand-managed queues
* optimisations to hashlib calls, remove python 2 checks, fork instead of spawn

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* fixed: issue 424 - pandas NaNs
* fixed: pandas deprecations and ruff linter suggestions
* fixed: issue 421 - detect pandas categorical type as categorical column

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* fixed: issue 414 - broken link
* fixed: issue 412 - timestamp types in ordinal encoder
* fixed: `importlib` instead of `pkg_resources`

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* added: ignore option for one-hot-encoding
* fixed: external dependency in unit test
* fixed: gaps in ordinal encoding if nan values are present
* fixed: sklearn compliance: add `feature_names_in_` attribute
* fixed: sklearn compliance: `get_feature_names_out` function has the correct signature
* fixed: add RankHotEncoder in documentation
* fixed: return correct mapping in one hot encoder `category_mapping` property (issue 256)
* refactor: quadratic runtime in ordinal encoder (issue 407)

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* added gray encoder
* added thermometer / rank-hot encoder
* introduce compatibility with sklearn 1.2
* compatibility with `feature_names_out_`
* remove boston housing dataset
* drop support for dataframes with non-homogenous data types in column names (i.e. having both string and integer column names)
* improve performance of hashing encoder
* improve catboost documentation
* fix inverse transform in baseN with special character column names (issue 392)
* fix inverse transform of ordinal encoder with custom mapping (issue 202)
* fix re-fittable polynomial wrapper (issue 313)
* fix numerical stability for target encoding (issue 377)
* change default parameters of target encoding (issue 327)
* drop support for sklearn 0.x

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* fix pypi sdist