Migrate ArbitraryOutlierCapper to narwhals, add polars support - #1034
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fit() only builds dicts from user input and validates variables/dtypes via check_numerical_variables (already narwhals-generic) - no numeric computation, so nothing to branch on there. The only pandas-specific lines were the feature_names_in_ assignment (X.columns.to_list(), a pandas-Index method), replaced with the same is_pandas-guarded pattern WinsorizerBase.fit() already uses (list(X.columns) for pandas, nw.from_native(X).columns - already list[str] - otherwise). transform() was already dataframe-agnostic via BaseOutlier._transform(); only its type hints changed (pd.DataFrame -> IntoDataFrame). Benchmarked fit+transform end-to-end at 10k/50k/100k rows x 1/2/10 columns: pandas-native (pre-migration) vs the migrated code on pandas were within noise of each other (~0.9-1.1x), and polars ran 2-4x faster than pandas on both. No pandas/polars branch needed - merged single path, consistent with the is_pandas-only-for-.columns precedent already set in WinsorizerBase. Confirmed the module needs zero pandas: reloaded artbitrary.py in isolation with sys.modules["pandas"] = None (simulating an uninstalled pandas) and ran fit/transform end-to-end on a polars frame - works, and int64 stays int64 for a same-dtype capping dict (the class docstring's own x1 example). Found, while doing so, a real dtype-preservation bug in the already- merged BaseOutlier._transform() (base_outlier.py, commit 71bf7cf on this branch's base) that predates this migration and is not introduced here: when a capping-dict spans columns of different dtypes that land in the same bound-group (e.g. max_capping_dict={"age": 50, "fare": 200} with age int64 and fare float64 - both "right_only"), the group's columns are stacked into one 2D array via to_numpy() before np.clip, which forces a common dtype and upcasts age to float64. The pre- narwhals code (verified against 71bf7cf^) clipped each column independently (X[feature] = X[feature].clip(...)), so int columns never picked up a neighboring float column's dtype. Confirmed this reproduces identically on both pandas and polars (same merged code path) and is untouched by this commit - it lives in base_outlier.py, shared with Winsoriser/OutlierTrimmer, out of this file's scope. Flagged separately rather than fixed here. Rewrote test_arbitrary_capper.py to one parametrized test per behavior over pd.DataFrame/pl.DataFrame (previously pandas-only), using nw.from_native(...).to_dict(as_series=False) for backend-agnostic assertions in place of pd.testing.assert_frame_equal, following the same pattern used for ReciprocalTransformer/ArcsinTransformer. Added a verified "With polars" section to the docs (float dtypes throughout, to sidestep the dtype-upcast issue above rather than put an unexplained surprise in a user-facing example); left the pre-existing pandas Titanic walkthrough untouched - no network access in this environment to re-verify the fetch_openml/CSV-backed output. Verified: tests/test_outliers full suite - 88 passed (up from 83, all 5 new instances are the added polars parametrizations), same 3 pre-existing check_estimator failures as the pre-migration baseline (numpy-array input, unrelated to this change). flake8 and mypy clean. sphinx -W build clean (only the pre-existing linkcode_resolve warning). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Bind the narwhals frame returned by check_X and set feature_names_in_ and n_features_in_ from it, instead of treating the check_X result as a native frame, mirroring the imputation and encoding modules. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
…r tests Replace the file-local _to_dict helper and parametrize decorators with the shared test structure: make_df fixture, isinstance(X, make_df) plus to_dict() checks, missing values written as None, and pytest.raises(match=re.escape(msg)). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
…ng test Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Migrates
ArbitraryOutlierCapperto narwhals with polars support.fit()only builds dicts from user input and validates viacheck_numerical_variables(already narwhals-generic) — no numeric computation. The only pandas-specific line wasfeature_names_in_ = X.columns.to_list(), replaced with the sameis_pandas-guarded patternWinsorizerBase.fit()already uses.transform()was already dataframe-agnostic viaBaseOutlier._transform(); only type hints changed (pd.DataFrame→IntoDataFrame).Merge vs split: benchmarked fit+transform end-to-end at 10k/50k/100k rows × 1/2/10 cols. pandas-native (pre-migration) vs migrated-on-pandas were within noise (~0.9–1.1x); polars ran 2–4x faster on both. No split — single merged path. Confirmed the module needs zero pandas (reloaded with
sys.modules["pandas"] = None, ran fit/transform on polars; int64 stays int64 for a same-dtype capping dict).Known pre-existing bug (flagged, not fixed here): in the already-merged
BaseOutlier._transform(), when a capping dict spans columns of different dtypes that land in the same bound-group (e.g.max_capping_dict={"age": 50, "fare": 200}, age int64 / fare float64, both "right only"), the group's columns are stacked into one 2D array viato_numpy()beforenp.clip, forcing a common dtype and upcasting age to float64. The pre-narwhals code clipped each column independently. Reproduces identically on both backends; lives inbase_outlier.py, shared with Winsoriser/OutlierTrimmer, out of this file's scope.Tests rewritten to one parametrized test per behaviour over
pd.DataFrame/pl.DataFrame, usingnw.from_native(...).to_dict(as_series=False)for backend-agnostic assertions. Docs "With polars" section added (float dtypes throughout, to sidestep the dtype-upcast issue above); pandas Titanic walkthrough untouched (no network in sandbox).Verified:
tests/test_outliers— 88 passed (up from 83), same 3 pre-existingcheck_estimatorfailures. flake8 / mypy clean, sphinx -W clean.Stacked on
narwhals-outliers-base(its own PR). Until that merges this PR's diff also contains the sharedBaseOutlier/WinsorizerBasecommit; review that one first.