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category works as expected.r3rr4rrrSrr r"Fr rrr rrrrrNr) rrrrrrrrr`rrr test_ohe_infrequent_three_levelss022    rc Cstdgddgddgddgdgj}td d d|d |}tdgdgdgg}td d gd d gd d gg|||jdd|d}tj t |d|dgdgg}W5QRXtd d gd d gg|dS)z5Test three levels and dropping the frequent category.r3rr4rrrSrr r"Frrr r!r%r&r'rN) rrrCrr)r r-rpr*warns UserWarning)rrrrr8rrrr.test_ohe_infrequent_three_levels_drop_frequents 2"rc Csztdgddgddgddgdgj}td d d|d }d |d d}tjt|d||W5QRXdS)z7Test three levels and dropping the infrequent category.r3rr4rrrSrr r"Frr rr r'Nr rrrr7test_ohe_infrequent_three_levels_drop_infrequent_errorss2rc Cstdgddgddgddgdgj}td d dd |}t|jddggdgdgdgdgg}td d d gd d d gd d d gd d d gg}||}t||dgg}d}t j t |d||W5QRXdS)zmTest that different parameters for combining 'a', and 'd' into the infrequent category works as expected.r3rr4rrrSrr r$F)r rrr rbadz.Found unknown categories \['bad'\] in column 0r'N) rrrCrr)r rr-r r*r+r,)rrrrrr8rrr(test_ohe_infrequent_handle_unknown_errors"2*  rcCstjdgddgdgtdj}tfddddggd d d ||}dgdgdgdgdgg}td d gd d gd d gd d gd d gg}||}t||dddgg}dgdgg}|D].}|j|d|td gd gg||qdS)zG'a' is the only frequent category, all other categories are infrequent.r3rrrYr?rrr4Fr"r6rr r rrrrN) rrrcrCrr)r-r rp)rrrrrrZdropsrrrr5test_ohe_infrequent_two_levels_user_cats_one_frequent,s&" (    rcCstjdgddgddgddgdgtd j}tddddggd d d d |}t|jdddggdgdgdgdgdgg}tddgddgddgddgddgg}||}t ||dddgdgdD}| |}t||dS)zFTest that the order of the categories provided by a user is respected.r3rr4rrrSrr r?Fr"r r6rr rrr rcSsg|] }|gqSrrrrrrr^sz.rr#N rrrcrCrr)r rr-r rrrrrrrrrrr(test_ohe_infrequent_two_levels_user_catsHs(( (   rc Cstjdgddgddgddgdgtd j}tddddggd d dd |}t|jddggdgdgdgdgd gg}tdddgdddgdddgdddgdddgg}||}t ||dgdgdgdgdgg}| |}t||dS)zTest that the order of the categories provided by a user is respected. In this case 'c' is encoded as the first category and 'b' is encoded as the second one.r3rr4rrrSrr r?Fr"rrrr rNrrrrr*test_ohe_infrequent_three_levels_user_catscs2( 2   rc Cstjdddddddddg dddddddddg f}tdddd}||ddgddgg}||}t|ddddgddddggdS) zaTest infrequent categories where feature 0 has infrequent categories, and feature 1 does not.rr r r rF)rrrN)rc_rr)r-r )rrrrrrrtest_ohe_infrequent_mixeds 2  r c Cstjdddddddddg dddddddddg dddddddddg f}tdddd }||}t|jdddgt|jdddgt|jdd |}td d d dddddg|ddddddddgddddddddgddddddddgddddddddgddddddddgddddddddgddddddddgddddddddgddddddddgg }t||dddgdddgg}| |}ddddddddgddddddddgg}t||| |}tj ddd gddd ggt d}t||tdddd  |}tjtdd| |W5QRXdddgdddgg}| |}ddddddddgddddddddgg}t||| |}tj dddgdddggt d}t||d S)z?Test infrequent categories with feature matrix with 3 features.rr r r rrSrAr"r6rr NZx0_0Zx0_3rZx1_0Zx1_5Zx1_infrequent_sklearnZx2_0Zx2_1r#rr?r$r&r')rrrrrr rr_r r-rrrcr)r*r+r,) rrrr`rr X_test_transrrrrr'test_ohe_infrequent_multiple_categoriess   (   ( r#c Cs(td}|jdddddddddg dddd d d dddg d d d gd}tdddd}||}t|jdddgt|jdddd gddddddgddddddgddddddgddddddgddddddgddddddgddddddgddddddgddddddgg }t|||jddgdd gd d d gd}ddddddgddddddgg}| |}t||| |}t j ddgddggt d}t|||jddgd dgd d d gd}| |}ddddddgddddddgg}t||| |}t j ddgddggt d}t||dS)zHTest infrequent categories with a pandas dataframe with multiple dtypes.rFr3frr4rr rrSrV)strrr%rcolumnsrAr"r!r rr?N)r*rJrKrrrr rr r-rrrrc) rLrrrrrr"rrrrr.test_ohe_infrequent_multiple_categories_dtypess\            r)rX)rrcCsptdgddgddgddgdgj}tfd d d |}|||dgg}t|d ggd S),All user provided categories are infrequent.r3rr4rrrSrr r"Frr N)rrrCrr)r-r rrrrrrr$test_ohe_infrequent_one_level_errors5s2 r,cCsftjdgdgtdj}tfddddggdd d ||}|dgdgg}t|d gd ggd S) r*rr r?rrr3r4Fr"rr N)rrrcrCrr)r-r r+rrr5test_ohe_infrequent_user_cats_unknown_training_errorsCs r-c CsHddgddgddgg}d}tjt|dtdd |W5QRXdS) NrOr rQr r z'`sparse` was renamed to `sparse_output`r'Fr)r*r FutureWarningrr))rr8rrr&test_one_hot_encoder_sparse_deprecatedTsr/zinput_dtype, category_dtypeZOOZOUZUOZUUSOZSUZSS array_typerrZ dataframec Cstjdgdgg|d}tjddg|dg}t|dd|}tdgdgdgdgg||d}||}tddgddgddgddgg}t||t|d|} | |}tdgdgdgdgg}t||d S) a"Check that encoding work with object, unicode, and byte string dtypes. Non-regression test for: https://github.com/scikit-learn/scikit-learn/issues/15616 https://github.com/scikit-learn/scikit-learn/issues/15726 https://github.com/scikit-learn/scikit-learn/issues/19677 r4r3r?Frsrr r5N) rrrr)rr-r rr ) r>Zcategory_dtyper1rr6rrrroerrrtest_encoders_string_categories]s  "  r3c Cshtjdgdggdd}tjddgddg}t|dd}td}tjt|d ||W5QRXd S) zCheck that this mixture of predefined categories and X raises an error. Categories defined as bytes can not easily be compared to data that is a string. r4r3Ur?SFrszjIn column 0, the predefined categories have type 'bytes' which is incompatible with values of type 'str_'.r'N) rrrrrr*r+r,r))rr6rr8rrr$test_mixed_string_bytes_categoricals|s r6cCsPtjdd|d|ggtdj}tddd|}|}t|ddd |gdS) Nr3r4r?Fr!rr Zx0_arZx0_)rrrcrCrr)r_r )rrrnamesrrr)test_ohe_missing_values_get_feature_namessr9c Cstd}|jddddgtjdddtjgtddd d gd }tdd ddd ddgd ddd dddgddd ddd dgd dddddd gg}t|}t||dS) NrFdogryr rr#r?)col1col2r;r<r&r ) r*rJrKrrrzfloatrur )rLdfexpected_df_transr}rrr%test_ohe_missing_value_support_pandass    r@ pd_nan_typepd.NAznp.nanc Cstd}|dkr|jntj}|d|jdd|ddgddi}td d d d gd d d d gd d d d gd d d d gd d d d gg}td |d }| |}t ||t |j d kst t|j d dd dddgt|j d d st dS)NrFrBr;rr3r4rir?rr Fr7r:)r*rJNArrzrKrrrrr lenrrr isnan)rAr rLpd_missing_valuer>r?rdf_transrrr1test_ohe_missing_value_support_pandas_categoricals*         rHc Csddgddgddgg}tdd|d}||}tdddgdddgdddgg}t||d d gg}tdddgg}d }tjt|d ||}W5QRXt||| |}t |tjddggt d dS)zZCheck drop='first' and handle_unknown='ignore'/'infrequent_if_exist' during transform.r3rr4r r rFrrr rr tFound unknown categories in columns \[0, 1\] during transform. These unknown categories will be encoded as all zerosr'r?N rrrrr r*rrr-rr rcr rrrrDrwarn_msgrrrr/test_ohe_drop_first_handle_unknown_ignore_warnss.     rNc Csddgddgddgg}tdd|d}||}tddddgddddgddddgg}t||d d gg}tddddgg}d }tjt|d ||}W5QRXt||| |}t |tjdd ggt dd S)zDCheck drop='if_binary' and handle_unknown='ignore' during transform.r3rr4r r rFrIrr rJr'Nr?rKrLrrr3test_ohe_drop_if_binary_handle_unknown_ignore_warnss.        rOc Csddgddgddgg}tdd|ddgddggd}||d dgg}tddgg}d }tjt|d ||}W5QRXt||d S) znCheck drop='first' and handle_unknown='ignore'/'infrequent_if_exist' during fit with categories passed in.r3rr4r r rF)rrr r6rzqFound unknown categories in columns \[0\] during transform. These unknown categories will be encoded as all zerosr'N) rr)rrr*rrr-r )r rrrrDrMrrrr'test_ohe_drop_first_explicit_categoriess  rPc Cstd}|jdddgdddgdddgd }td d }|jdd d }tjt|d||W5QRX||tjt|d| |W5QRXdS)zJRaise informative error message when pandas output and sparse_output=True.rFr r r rr4)r3r4r3r&Trr-zxPandas output does not support sparse data. Set sparse_output=False to output pandas DataFrames or disable pandas outputr'N) r*rJrKr set_outputr+r,rr)r-)rLr>rr8rrr'test_ohe_more_informative_error_message7s $   rSc CsXttjdddggj}ttjd}dtj}tjt|d| |W5QRXdS)zDTest ordinal encoder with nan passthrough fails when dtype=np.int32.rrr?zdThere are missing values in features \[0\]. For OrdinalEncoder to encode missing values with dtype: r'N) rrrzrCrint32r*r+r,r))rr2r8rrrBtest_ordinal_encoder_passthrough_missing_values_float_errors_dtypeKs   rUencoded_missing_valuercCstjtjdddggtjdj}t|d|}t|jdks@t t |jdddtjg| |}t ||gdgdgdgg| |}t ||dS) z.Test ordinal encoder with nan on float dtypes.rrr?rVr rrN) rrrzrrCrr)rDrrr r-r)rVrr2rr rrr5test_ordinal_encoder_passthrough_missing_values_floatYs  rXc Cs$td}|dkr|jntj}|d|jdd|ddgddi}t|d |}t |j d ksbt t |j d d d dddgt |j d dst ||}t|dgdg|gdgdgg||}|jdkst t |d dd fddgt |d d d fddgt |ds t d S)z0Check ordinal encoder is compatible with pandas.rFrBr;rr3r4rir?rWr rNr r:@rr)rr r r)r*rJrCrrzrKrrr)rDrrr rEr-r rr)rArVrLrFr>r2rGr rrr=test_ordinal_encoder_missing_value_support_pandas_categoricalks$   rZrYzobject-None-missing-valuezobject-nan-missing_valueznumeric-missing-valuec Cstt|d}tdgtjgg}t||||jdj|ksBtt|d}t j t dd| |W5QRXdS)z.Test ordinal encoder for specified categories.r5rrr&r'N) rrrrzr rrr@rr*r+r,r))rr0rrr2rrrr=test_ordinal_encoder_specified_categories_missing_passthroughs&  r[zX, expected_X_trans, X_testrrcCs8tddd}||}t||t||dggdS)z>Test the interaction between missing values and handle_unknownrr:rgN)rrr r-)rZexpected_X_transrr2rrrr/test_ordinal_encoder_handle_missing_and_unknowns   r\c Cstdddgdddgg}t|}t}d}tjt|d||W5QRXtjt|d| |W5QRX| |}t|}tjt|d| |W5QRXdS)zCheck that we raise proper error with sparse input in OrdinalEncoder. Non-regression test for: https://github.com/scikit-learn/scikit-learn/issues/19878 r r r rz6A sparse matrix was passed, but dense data is requiredr'N) rrrZ csr_matrixrr*r+rmr)rr)rZX_sparseencoderrnrrrrrtest_ordinal_encoder_sparses   r^c Cstddddddgddtjf}tdddggddd }||tdddggd d }tjtd d ||W5QRXdS)zCheck OrdinalEncoder.fit works with unseen category when `handle_unknown="use_encoded_value"`. Non-regression test for: https://github.com/scikit-learn/scikit-learn/issues/19872 rr r rNr:rr)r6r rr$rr&r')rrZnewaxisrr)r*r+r,)rr2rrr-test_ordinal_encoder_fit_with_unseen_categorys$  r_rZAAOr4rcCs4tddd}||||}t|ddggdS)zChecks that `OrdinalEncoder` transforms string dtypes. Non-regression test for: https://github.com/scikit-learn/scikit-learn/issues/19872 rirrN)rr)r-r )rrr7rrrr1test_ordinal_encoder_handle_unknown_string_dtypes s   racCsftddddgdd}t|}t|jtj|ddj| |}t|dgd gd gdggd S) zCheck that `OrdinalEncoder` accepts Python integers that are potentially larger than 64 bits. Non-regression test for: https://github.com/scikit-learn/scikit-learn/issues/20721 l HP 1&l H]viel :?i}GalIRK2e6kr:r r)Zaxisr r N) rrr;rr)r rsortrCr-)rr]rrrr#test_ordinal_encoder_python_integer's  rccCsLtd}dddg}|jdddgg|d}t|}|}t||d S) z-Check feature names out is same as the input.rFr4rr3r r r r&N)r*rJrKrr)r_r )rLr8rr7Zfeature_names_outrrr.test_ordinal_encoder_features_names_out_pandas;s    rdcCstjdgdgtjggtd}tdtjdd|}||}t|dgdgdggtjd gtjggtd}||}t|tjgdgg||}|ddd kst t |ddst d S) zECheck interactions between encode_unknown and missing value encoding.r3r4r?rr rrVrr rN) rrrzrcrr)r-r rrrE)rr2rrr" X_roundtriprrr0test_ordinal_encoder_unknown_missing_interactionGs    rh with_pandasc Cstjddgddgdtjggtd}d}|rPtd}|j|d d gd }|d }n|d }tdd}tjt |d| |W5QRXdS)zXCheck OrdinalEncoder errors when encoded_missing_value is used by an known category.r3r:r4ryrr?zTencoded_missing_value \(1\) is already used to encode a known category in features: rFletterZpetr&z \['pet'\]z\[1\]r rWr'N) rrrzrcr*rJrKrr+r,r))rir error_msgrLr2rrr0test_ordinal_encoder_encoded_missing_value_errores"   rlz4X_train, X_test_trans_expected, X_roundtrip_expected1c Cstdtjtjd|}tdgtjgdgg}||}t||||}|jd}t |D]V}||df} ||df} | dkr| dkst q`t | rt | st q`| | ks`t q`dS)znCheck transform when unknown_value and encoded_missing_value is nan. Non-regression test for #24082. rrfrmr4rN) rrrzr)rr-r rrrrrrE) rZX_test_trans_expectedZX_roundtrip_expectedr2rr"rgZ n_samplesrZ expected_valvalrrr9test_ordinal_encoder_unknown_missing_interaction_both_nans(       roc Cstd}|ddgddgd}t}|jddd}tjt|d ||W5QRXtd d jd d}td d jdd}||}||}t| |t | |j d S)z*Check OneHotEncoder works with set_output.rFr3r4r r rGrQz*Pandas output does not support sparse datar'FrdefaultN) r*rJrKrrRr+r,rr to_numpyr r_r')rLrMrr(Z ohe_defaultZ ohe_pandas X_defaultX_pandasrrrtest_one_hot_encoder_set_outputs    rtcCsttd}|ddgddgd}tjdd}tjdd}||}||}t||t| |j d S) z+Check OrdinalEncoder works with set_output.rFr3r4r r rGrprQN) r*rJrKrrRrr rqr r_r')rLrMZ ord_defaultZ ord_pandasrrrsrrrtest_ordinal_set_outputs   rucCszdddddgddgg}t|d}|ddggt|t|jksFtt|jD]$\}}|jtksftt|||qPd S) zjCheck that the categories_ dtype is `object` for string categories Regression test for gh-25171. asZmmasZeasZrasZacsrm2r5N) rr)rDrr enumerater@rcr )r6r7nryrrr test_predefined_categories_dtypes rzcCs~tjdgdgtjggtd}tdd|}t|dgdgdggtddd |}td gg}||}t|dggd S) zBCheck missing value or unknown encoding can equal the cardinality.r:ryr?r rWr rrrsnakeN) rrrzrcrrr r)r-)rrr7rrrr1test_ordinal_encoder_missing_unknown_encoding_maxs r|cCstjdgddgddgddgddgdgtdj}tdd d d |}t|d d ddg|jd|j ddkst tjdgddgddgdgtdj}tdd dd |}t|dg|jd|j ddkst tjdgddgddgddgddgdgtdj}tdd dgd |}t|dd ddg|jd|j ddks|t tdd dd |}t|dd d ddg|j dkst dS)zkCheck drop_idx is defined correctly with infrequent categories. Non-regression test for gh-25550. r3r r4r#rrrr?Fr)rrrrZx0_dZx0_errrSrrN) rrrcrCrr)r r_rrr)rrrrr#test_drop_idx_infrequent_categoriess<2 ,2  r}cCstdgddgddgddgdgj}tfd d d ||}t|jddddggt|jddggdgdgdgdgd gg}d gdgdgd gd gg}||}t ||| |}dgdgdgdgdgg}t||dS)zGTest parameters for grouping 'a', and 'd' into the infrequent category.r3rr4rrrSrr rr:rrr rr rN) rrrCrr)r rrr-r r)rrordinalrexpected_transrr expected_inverserrr,test_ordinal_encoder_infrequent_three_levelss.2   rcCstjdgddgddgddgdgtd j}tddddggdd d d |}t|jddddggt|jddggdgdgdgdgd gg}dgdgdgdgd gg}| |}t ||| |}dgdgdgdgdgg}t||dS)zTest that the order of the categories provided by a user is respected. In this case 'c' is encoded as the first category and 'b' is encoded as the second one. r3rr4rrrSrr r?rr:)r6rr rrr r rrN) rrrcrCrr)r rrr-r r)rr~rrrr rrrr6test_ordinal_encoder_infrequent_three_levels_user_catsBs4(    rc Cstdddddddddg dddddddddg f}tdd|}t|jdddg|jddkshtddgddgg}ddgddgg}||}t||| |}tj ddgddggt d}t||dS) zETest when feature 0 has infrequent categories and feature 1 does not.rr r r rNrr?) rZ column_stackrr)r rrr-r rrrc)rr~rrrr rrrr%test_ordinal_encoder_infrequent_mixedfs2   rc CsVtd}|ddddg}|jdddddddd d g d d d d d dd d d g |jdgddgd dgdg|dddddgd}td d|}t|jd dd gt|jdd d dgt|jdddg|jdd ddgdd d d g|jdgdgdgdg|dddddgd}ddd gdddgdddgd d dgg}| |}t ||dS)zHTest infrequent categories with a pandas DataFrame with multiple dtypes.rFbirdryr:r{r3r$rr4rr rrSrVr#r?)r%rrr%rrr&rr r N) r*rJZCategoricalDtyperKrrr)r rr-r )rLZcategorical_dtyperr~rrrrrr:test_ordinal_encoder_infrequent_multiple_categories_dtypes{s:      $ rcCstjdgddgddgddgdtjggtd j}td d d dd |}t|jdddggtjdgdgdgdgd gtjggtd }dgdgdgdgd gdgg}| |}t ||dS)zJCheck behavior of unknown_value and encoded_missing_value with infrequent.r3rr4rrrSrr r?rr )r rrrVrr rN) rrrzrcrCrr)r rr-r )rr~rrrrrr.test_ordinal_encoder_infrequent_custom_mappings"0( rcCstjdgddgddgddgdgtd j}tf|d d d |}td d d |}dgdgdgdgd gg}t||||dS)zMAll categories are considered frequent have same encoding as default encoder.r3rr4rrrSrr r?rr:rrNrrrcrCrr)r r-)rrZadjusted_encoderZdefault_encoderrrrr!test_ordinal_encoder_all_frequents, ( rdcCstjdgddgddgddgdgtd j}tf|d d d |}dgdgdgdgd gg}t||dgdgdgdgd ggdS)zAWhen all categories are infrequent, they are all encoded as zero.r3rr4rrrSrr r?rr:rrrNr)rrr]rrrr#test_ordinal_encoder_all_infrequents ( rcCstjtjgddgddgddgdggtdj}td d |}tjdddtjggtdj}||}t|d gd gd gtjggdS)z5Check behavior when missing value appears frequently.rr:rSryrr{deerr?r rr rr N rrrzrcrCrr)r-r rr~rrrrr-test_ordinal_encoder_missing_appears_frequents, rcCstjtjgdgddgddgdgdgdd gdgtd j}td d |}tjddgdd gtjd gdd gddggtd }||}t|d dgd dgtjdgddgddggdS)z7Check behavior when missing value appears infrequently.r:rSryrr{rredrgreenr?r#)rr r rNrrrrr/test_ordinal_encoder_missing_appears_infrequents$& r)}rnumpyrr*ZscipyrZsklearn.exceptionsrZsklearn.preprocessingrrZ sklearn.utilsrZsklearn.utils._testingrr r rmarkZ parametrizer2r9r<rTZfloat32rrErNrardrorrrurrcrzr=r~rrrrrrrrZstr_rrCrrrrrrrrrrrrrrrrrrrrrrrrr rrrrrrrrr r#r)r,r-r/r3r6r9r@rHrNrOrPrSrUrXrZr[r\r^r_rarcrdrhrlrBrortrurzr|r}rrrrrrrrrrrrrs        <       /0&     & &* !       -8               $           $[A       % $     "       !    $  $  0