Mh0SSKJr SSKrSSKJrJrJr SSKrSSK J r J r SSK Jr SSKJr SSKJr SSKJr SS KJr SS KJrJr \(aSSKrSS KJrJrJrJrJ r \"S S \55r!SSSjjr""SS\5r#g)) annotationsN) TYPE_CHECKINGClassVarcast)libmissing) is_list_like)register_extension_dtype)isna)ops)masked_accumulations)BaseMaskedArrayBaseMaskedDtype)DtypeDtypeObjSelfnpttype_tc\rSrSr%SrSrS\S'\SSj5r\SSj5r \SSj5r \ SS j5r SS jr \SS j5r\SS j5rSS jrSrg) BooleanDtype(a  Extension dtype for boolean data. .. warning:: BooleanDtype is considered experimental. The implementation and parts of the API may change without warning. Attributes ---------- None Methods ------- None Examples -------- >>> pd.BooleanDtype() BooleanDtype booleanz ClassVar[str]namec"[R$N)npbool_selfs L/var/www/html/env/lib/python3.13/site-packages/pandas/core/arrays/boolean.pytypeBooleanDtype.typeDs xxcg)Nbrs r kindBooleanDtype.kindHsr#c.[R"S5$)Nbool)rdtypers r numpy_dtypeBooleanDtype.numpy_dtypeLsxxr#c[$)zI Return the array type associated with this dtype. Returns ------- type ) BooleanArray)clss r construct_array_type!BooleanDtype.construct_array_typePs r#cg)Nrr&rs r __repr__BooleanDtype.__repr__[sr#cgNTr&rs r _is_booleanBooleanDtype._is_boolean^r#cgr7r&rs r _is_numericBooleanDtype._is_numericbr:r#cSSKnURUR"5:waCURR UR5(d[ SURS35e[ XR5(aU/n[U5nOURnUR5nURR UR5(a=[R"U[S9n[R"U[S9n[Xe5$/nUHnUR!5n URR#UR[U5SU S/UR$S9R'SS 9nUR(S:waOURR#UR[U5SU S/UR$S9R'SS 9nU)nO"[R*"[U5[S9n[Xe5n UR-U 5 M U(dN[[R."/[RS9[R."/[RS95$[R1U5$) z9 Construct BooleanArray from pyarrow Array/ChunkedArray. rNz$Expected array of boolean type, got z insteadr+)offsetF)zero_copy_only)pyarrowr!rtypesis_null TypeError isinstanceArraylenchunkslengthronesr*emptyr/buffers from_buffersrAto_numpy null_countzerosappendarray_concat_same_type) rrTrCrJrKmaskdataresultsarrbuflistbool_arrs r __from_arrow__BooleanDtype.__from_arrow__fs  :: (1F1Fuzz1R1RB5::,hWX X e]] + +WFZF\\F\\^F ==  , ,776.D88F$/D+ +CkkmG''44#c(T71:$6szz5heh, ~~"++88HHc#hwqz(:3::9(%(0uxxC5#D/H NN8 $ 288,bhhr.J  11': :r#r&N)returnr!)r^str)r^znp.dtype)r^ztype_t[BooleanArray]r^r*)rTz$pyarrow.Array | pyarrow.ChunkedArrayr^r/)__name__ __module__ __qualname____firstlineno____doc__r__annotations__propertyr!r'r, classmethodr1r4r8r<r\__static_attributes__r&r#r rr(s,$D-#  /;9/; /;r#rc[U[5(aOUb [S5eURURpU(a UR 5nUR 5nX4$Sn[U[ R5(a7UR[ R:XaU(aUR 5nGO[U[ R5(aURRS;a[U5n[ R"[U5[S9nX)R[5XC)'[ R "XC)RUR5X):H5(d [#S5eUnO[ R$"U[&S9n[(R*"USS9nSnUS U-;a [#S5e[-S [U55n[ R"[U5[S9nXS)R[5X)'Xg;aU[ R "X)R[.5XS)R[.5:H5(d [#S5eUc'Uc$[ R"UR0[S9nOUcUnO}[U[ R5(a>UR[ R:Xa UbX-nO8U(aUR 5nO [ R2"U[S9nUbX-nUR0UR0:wa [S 5eX4$) z Coerce the input values array to numpy arrays with a mask. Parameters ---------- values : 1D list-like mask : bool 1D array, optional copy : bool, default False if True, copy the input Returns ------- tuple of (values, mask) Nz'cannot pass mask for BooleanArray inputiufcbr?zNeed to pass bool-like valuesTskipna)floatingintegerzmixed-integer-float)rrMnpt.NDArray[np.bool_]z&values.shape and mask.shape must match)rGr/ ValueError_data_maskcopyrndarrayr+rr'r rRrIr*astypeallrFasarrayobjectr infer_dtyperfloatshaperT)valuesrVrt mask_values values_bool values_objectinferred_dtype integer_likes r coerce_to_arrayrs"&,''  FG G||V\\ [[]F99;D|K&"**%%&,,"((*B [[]F FBJJ ' 'FLL,=,=,H6l hhs6{$7 $*<$8$?$?$E L!vv  % , ,V\\ :f\>R R  ;< < 68 tDE !5 !D D;< <2D4GH #f+T2,\:AA$G|  * FF|$++E2 .55e<=   ;< < | +xx D1  dBJJ ' 'DJJ"((,B&)99;D88D-D&) ||tzz!ABB <r#cV^\rSrSrSrSrSrSr1Skr1Skr \ SU4Sjj5r SSU4Sjjjr \ SS j5r\ S SS S S .SS jj5r\R"\R&\\R*4r\ SS .SSjj5rSrSS.SSjjrSrU=r$)r/a Array of boolean (True/False) data with missing values. This is a pandas Extension array for boolean data, under the hood represented by 2 numpy arrays: a boolean array with the data and a boolean array with the mask (True indicating missing). BooleanArray implements Kleene logic (sometimes called three-value logic) for logical operations. See :ref:`boolean.kleene` for more. To construct an BooleanArray from generic array-like input, use :func:`pandas.array` specifying ``dtype="boolean"`` (see examples below). .. warning:: BooleanArray is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- values : numpy.ndarray A 1-d boolean-dtype array with the data. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values (True indicates missing). copy : bool, default False Whether to copy the `values` and `mask` arrays. Attributes ---------- None Methods ------- None Returns ------- BooleanArray Examples -------- Create an BooleanArray with :func:`pandas.array`: >>> pd.array([True, False, None], dtype="boolean") [True, False, ] Length: 3, dtype: boolean FT>1TRUETruetrue1.0>0FALSEFalsefalse0.0cD>[TU]X5n[5UlU$r)super _simple_newr_dtype)r0r}rVresult __class__s r rBooleanArray._simple_new-s $V2$  r#c>[U[R5(aUR[R:Xd [ S5e[ 5Ul[TU]%XUS9 g)NzIvalues should be boolean numpy array. Use the 'pd.array' function insteadrt) rGrrur+rrFrrr__init__)rr}rVrtrs r rBooleanArray.__init__3sT62::..6<<2883K2 #n  D1r#cUR$rrrs r r+BooleanArray.dtype>s {{r#N)r+rt true_values false_valuescF^ ^ URRU=(d /5m URRU=(d /5m SU U 4Sjjn[R"U[ S9n[ U5n[[XgU)55Xx)'URXrUS9$)Nc<>UT;agUT;ag[US35e)NTFz cannot be cast to bool)rq)sfalse_values_uniontrue_values_unions r map_string:BooleanArray._from_sequence_of_strings..map_stringOs.%%(( A3&=!>??r#r?)r+rtr`) _TRUE_VALUESunion _FALSE_VALUESrrTryr listmap_from_sequence) r0stringsr+rtrrrscalarsrVrrs @@r _from_sequence_of_strings&BooleanArray._from_sequence_of_stringsBs ,,22;3D"E ..44\5GRH @ @((7&1G}c*ten=>!!'T!BBr#rc2U(aUS:Xde[XS9$)Nrr)r)r0valuer+rts r _coerce_to_arrayBooleanArray._coerce_to_array^s  I% %%u00r#c$URS;de[R"U5nSn[U[5(aUR UR pAO|[U5(a=[R"USS9nURS:a [S5e[USS9upO/[U[R5(aUR5nU(aPU[R La=[R""U5(d"[%S['U5RS 35eU(d#[)U5[)U5:wa [+S 5eURS ;a/[,R."UR XR U5upTOmURS ;a/[,R0"UR XR U5upTO.[,R2"UR XR U5upTUR5XT5$) N>or_xorand_ror_rxorrand_r*r?r@z(can only perform ops with 1-d structuresFrz+'other' should be pandas.NA or a bool. Got z instead.zLengths must match>rr>rr)rar is_scalarrGr/rrrsr rrxndimNotImplementedErrorrritem libmissingNAis_boolrFr!rIrqr kleene_or kleene_and kleene_xor_maybe_mask_result)rotheropother_is_scalarrVrs r _logical_methodBooleanArray._logical_methodfs{{MMMM--. e\ * *++u{{4 % JJuF3EzzA~)*TUU)%e>$**eZZNLFD>>$**eZZNLF&&v44r#rlc URnURnUS;a.[[U5nU"XE4SU0UD6upEUR XE5$SSKJn U"UR[5U5R"U4SU0UD6$)N)cummincummaxrmr) IntegerArray) rrrsgetattrr rpandas.core.arraysrrvint _accumulate)rrrmkwargsrWrVrrs r rBooleanArray._accumulateszzzz ' '-t4BD@v@@JD##D/ / 7 C 0$7CC#'- r#r)r} np.ndarrayrVrpr^r)F)r}rrVrrtr*r^None)r^r) rz list[str]r+z Dtype | Nonertr*rlist[str] | Nonerrr^r/)r+rrtr*r^tuple[np.ndarray, np.ndarray])rr_rmr*r^r)rarbrcrdre_internal_fill_value _truthy_value _falsey_valuerrrhrrrgr+rrrunumbersNumberr*r_HANDLED_TYPESrrrri __classcell__)rs@r r/r/sX1h!MM7L;M BG 2  2(2 2:> 2  2 2 #(,)-CC C  C & C'C CC2jj'..$AN5:1&1.21 &11!5H,0$( r#r/)NF)rtr*r^r)$ __future__rrtypingrrrnumpyr pandas._libsrrrpandas.core.dtypes.commonr pandas.core.dtypes.dtypesr pandas.core.dtypes.missingr pandas.corer pandas.core.array_algosr pandas.core.arrays.maskedrrrCpandas._typingrrrrrrrr/r&r#r rs"  3>+8 l;?l;l;`%*T!T"Tnh?hr#