Migrate PowerTransformer to narwhals, add polars support - #1005
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Pure elementwise math (x ** exp), so followed the same precedent as ArcsinTransformer/ReciprocalTransformer (same module, same shape of problem): extract the transform columns to a single numpy array via narwhals' to_numpy(), apply np.power once, reassign via nw.new_series + with_columns. Benchmarked narwhals-on-pandas vs the old pandas-native .loc-assignment across 10k-100k rows and 1-10 columns: narwhals-on-pandas ran in 0.47x-0.77x of the old runtime (avg 0.58x, i.e. ~1.7x faster), narwhals-on-polars faster still (avg 0.42x) - consistent with both sibling transformers, so no pandas/polars branch was added; both transform() and inverse_transform() use the same merged narwhals path. Rewrote test_power_transformer.py to one parametrized test per behavior over pandas/polars input (previously pandas-only, relying on the global df_vartypes/df_na fixtures), replaced with local DATA/DATA_NA dicts, same pattern as test_reciprocal_transformer.py. All expected values recomputed and verified against actual output. Verified every code example already in docs/user_guide/transformation/PowerTransformer.rst against current output (including the fetch_openml/Ames-housing walkthrough - network was available this run) - all matched exactly, no doc fixes needed. Added a verified "With polars" section before the Considerations heading. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Pure elementwise math (x ** exp), so followed the same precedent as ArcsinTransformer/ReciprocalTransformer (same module, same shape of problem): extract the transform columns to a single numpy array via narwhals' to_numpy(), apply np.power once, reassign via nw.new_series + with_columns. Benchmarked narwhals-on-pandas vs the old pandas-native .loc-assignment across 10k-100k rows and 1-10 columns: narwhals-on-pandas ran in 0.47x-0.77x of the old runtime (avg 0.58x, i.e. ~1.7x faster), narwhals-on-polars faster still (avg 0.42x) - consistent with both sibling transformers, so no pandas/polars branch was added; both transform() and inverse_transform() use the same merged narwhals path. Rewrote test_power_transformer.py to one parametrized test per behavior over pandas/polars input (previously pandas-only, relying on the global df_vartypes/df_na fixtures), replaced with local DATA/DATA_NA dicts, same pattern as test_reciprocal_transformer.py. All expected values recomputed and verified against actual output. Verified every code example already in docs/user_guide/transformation/PowerTransformer.rst against current output (including the fetch_openml/Ames-housing walkthrough - network was available this run) - all matched exactly, no doc fixes needed. Added a verified "With polars" section before the Considerations heading. Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
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Pure elementwise math (x ** exp), so followed the same precedent as ArcsinTransformer/ReciprocalTransformer (same module, same shape of problem): extract the transform columns to a single numpy array via narwhals' to_numpy(), apply np.power once, reassign via nw.new_series + with_columns.
Benchmarked narwhals-on-pandas vs the old pandas-native .loc-assignment across 10k-100k rows and 1-10 columns: narwhals-on-pandas ran in 0.47x-0.77x of the old runtime (avg 0.58x, i.e. ~1.7x faster), narwhals-on-polars faster still (avg 0.42x) - consistent with both sibling transformers, so no pandas/polars branch was added; both transform() and inverse_transform() use the same merged narwhals path.
Rewrote test_power_transformer.py to one parametrized test per behavior over pandas/polars input (previously pandas-only, relying on the global df_vartypes/df_na fixtures), replaced with local DATA/DATA_NA dicts, same pattern as test_reciprocal_transformer.py. All expected values recomputed and verified against actual output.
Verified every code example already in
docs/user_guide/transformation/PowerTransformer.rst against current output (including the fetch_openml/Ames-housing walkthrough - network was available this run) - all matched exactly, no doc fixes needed. Added a verified "With polars" section before the Considerations heading.