+ Ŝif4L^RIHt^RIt^RIHtHtHtHt^RIt ^RI H t H t ^RIHt^RIHt^RIHt^RIHt^R IHt^R IHt^R IHtHt]'d^RIt^R IHtH t H!t!^R IH"t"]]!R4!RR]444t#RRRllt$]!R4!RR]44t%R#)) annotationsN) TYPE_CHECKINGClassVarSelfcast)libmissing) set_module) is_list_like)register_extension_dtype)isna)ops)masked_accumulations)BaseMaskedArrayBaseMaskedDtype)DtypeObjnpttype_t)ExtensionDtypepandasc]tRt^*t$RtRtR]R&Rt]RRl4t ]RR l4t ]R R l4t R R lt RRlt ]RRl4t]RRl4tRRltRtR#) BooleanDtypea Extension dtype for boolean data. This is a pandas Extension dtype for boolean data with support for missing values. BooleanDtype is the dtype companion to :class:`.BooleanArray`, which implements Kleene logic (sometimes called three-value logic) for logical operations. See :ref:`boolean.kleene` for more. .. warning:: BooleanDtype is considered experimental. The implementation and parts of the API may change without warning. Attributes ---------- None Methods ------- None See Also -------- arrays.BooleanArray : Array of boolean (True/False) data with missing values. Int64Dtype : Extension dtype for int64 integer data. StringDtype : Extension dtype for string data. Examples -------- >>> pd.BooleanDtype() BooleanDtype >>> pd.array([True, False, None], dtype=pd.BooleanDtype()) [True, False, ] Length: 3, dtype: boolean >>> pd.array([True, False, None], dtype="boolean") [True, False, ] Length: 3, dtype: boolean booleanz ClassVar[str]nameFcV^8dQhRR/#)returntype)formats"c/Users/mibo/.openclaw/workspace/.venv-ak/lib/python3.14/site-packages/pandas/core/arrays/boolean.py __annotate__BooleanDtype.__annotate__`sdc "\P#N)npbool_selfs&r!rBooleanDtype.type_s xxr$cV^8dQhRR/#rrstrr)r s"r!r"r#dscr$c R#)brr)s&r!kindBooleanDtype.kindcsr$cV^8dQhRR/#)rrznp.dtyper)r s"r!r"r#hs  X r$c .\P!R4#)bool)r'dtyper)s&r! numpy_dtypeBooleanDtype.numpy_dtypegsxxr$cV^8dQhRR/#)rrztype_t[BooleanArray]r)r s"r!r"r#ks&:r$c \#)zI Return the array type associated with this dtype. Returns ------- type ) BooleanArrayr)s&r!construct_array_type!BooleanDtype.construct_array_typeks r$cV^8dQhRR/#r-r)r s"r!r"r#us#r$c R#)rrr)s&r!__repr__BooleanDtype.__repr__usr$cV^8dQhRR/#rrr5r)r s"r!r"r#yTr$c R#Trr)s&r! _is_booleanBooleanDtype._is_booleanxr$cV^8dQhRR/#rCr)r s"r!r"r#}rDr$c R#rFrr)s&r! _is_numericBooleanDtype._is_numeric|rIr$c V^8dQhRRRR/#)rarrayz$pyarrow.Array | pyarrow.ChunkedArrayrr;r)r s"r!r"r#s/;/;9/; /;r$c V^RIpVPVP!48wdEVPP VP4'g\ RVP R24h\ WP4'dV.p\V4pMVPpVP4pVPP VP4'dD\P!V\R7p\P!V\R7p\We4#.pVEFpVP!4p VPP#VP\V4RV ^,.VP$R7P'RR7pVP(^8wdZVPP#VP\V4RV ^,.VP$R7P'RR7pV(pM%\P*!\V4\R7p\We4p VP-V 4EK V'gU\\P.!.\PR7\P.!.\PR74#\P1V4#)z9 Construct BooleanArray from pyarrow Array/ChunkedArray. Nz$Expected array of boolean type, got z insteadr6)offsetF)zero_copy_only)pyarrowrr(typesis_null TypeError isinstanceArraylenchunkslengthr'onesr5emptyr;buffers from_buffersrRto_numpy null_countzerosappendrO_concat_same_type) r*rOrTr[r\maskdataresultsarrbuflistbool_arrs && r!__from_arrow__BooleanDtype.__from_arrow__s  :: (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$rN)__name__ __module__ __qualname____firstlineno____doc__r__annotations___internal_fill_valuepropertyrr1r7r<r@rGrLrl__static_attributes__rr$r!rr*s)V$D-#!  /;/;r$rc V^8dQhRRRR/#)rcopyr5rtuple[np.ndarray, np.ndarray]r)r s"r!r"r"s RR!R"Rr$c0\V\4'dRVe \R4hVPVPrV'd!VP 4pVP 4pW3#Rp\V\ P4'd:VP\ P8XdV'dVP 4pEM\V\ P4'dVPPR9d\V4p\ P!\V4\R7pW(,P\4WC(&\ P !WC(,PVP4W(,8H4'g \#R4hTpEM \ P$!V\&R7p\(P*!VRR7pR pVRR .VO59d \#R4h\-R \V44p\ P!\V4\R7pWS(,P\4W(&Wg9d_\ P !W(,P\.4WS(,P\.48H4'g \#R4hVf,Vf(\ P!VP0\R7pMVfTpM\V\ P4'dFVP\ P8Xd'Ve W,pMAV'dVP 4pM(\ P2!V\R7pVe W,pVP0VP08wd \R 4hW3#) 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 inputiufcbrQzNeed to pass bool-like valuesT)skipnarr^npt.NDArray[np.bool_]z&values.shape and mask.shape must match)floatingintegerzmixed-integer-float)rXr; ValueError_data_maskrxr'ndarrayr6r(r1r rcrZr5astypeallrWasarrayobjectr infer_dtyperfloatshaperO)valuesrfrx 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 )W!D|!D D;< <2D4GH #f+T2,\:AA$G|  * FF|$++E2 .55e<=   ;< < | +xx D1  D"** % %$***@  "%D 99;DxxD)  "%D ||tzz!ABB <r$z pandas.arraysc "a]tRtRtRt0Rmt0Rmt]RV3Rll4tRRV3Rlllt ] RR l4t ]R RR R R R RR /RRll4t ] P]P ]] P$3t]R R/RRll4tRtRR/RRlltRtV;t#)r;ia Array of boolean (True/False) data with missing values. This is a pandas Extension array for boolean data, under the hood represented by 2 numpy arrays: a boolean array with the data and a boolean array with the mask (True indicating missing). BooleanArray implements Kleene logic (sometimes called three-value logic) for logical operations. See :ref:`boolean.kleene` for more. To construct a BooleanArray from generic array-like input, use :func:`pandas.array` specifying ``dtype="boolean"`` (see examples below). .. warning:: BooleanArray is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- values : numpy.ndarray A 1-d boolean-dtype array with the data. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values (True indicates missing). copy : bool, default False Whether to copy the `values` and `mask` arrays. Attributes ---------- None Methods ------- None Returns ------- BooleanArray See Also -------- array : Create an array from data with the appropriate dtype. BooleanDtype : Extension dtype for boolean data. Series : One-dimensional ndarray with axis labels (including time series). DataFrame : Two-dimensional, size-mutable, potentially heterogeneous tabular data. Examples -------- Create a BooleanArray with :func:`pandas.array`: >>> pd.array([True, False, None], dtype="boolean") [True, False, ] Length: 3, dtype: boolean c$V^8dQhRRRRRR/#)rr np.ndarrayrfr}rrr)r s"r!r"BooleanArray.__annotate__Gs"3HTr$c D<\SV`W4p\4VnV#r&)super _simple_newr_dtype)clsrrfresult __class__s&&& r!rBooleanArray._simple_newFs $V2$  r$Fc(V^8dQhRRRRRRRR/#)rrrrfrxr5rNoner)r s"r!r"rLs, 2 2  2(2 2:> 2  2r$c <\V\P4'd VP\P8Xg \ R4h\ 4Vn\SV`%WVR7R#)zIvalues should be boolean numpy array. Use the 'pd.array' function insteadrxN) rXr'rr6r(rWrrr__init__)r*rrfrxrs&&&&r!rBooleanArray.__init__LsT62::..6<<2883K2 #n  D1r$cV^8dQhRR/#)rrrr)r s"r!r"rXs|r$c VP#r&rr)s&r!r6BooleanArray.dtypeWs {{r$rx true_valuesN false_values none_valuesc4V^8dQhRRRRRRRRR RR RR R /#) rstringsz list[str]r6rrxr5rzlist[str] | Nonerrrr;r)r s"r!r"r\sYCCC C  C & C'C&C Cr$c paa a VPPT;'g.4o VPPT;'g.4o Sf.oRV VV 3Rllp\P!V\ R7p\ V4p \\WxV (,44W(&VPWVR7#)NcV^8dQhRR/#)rrz bool | Noner)r s"r!r".__annotate__ls @ @[ @r$cV<VS9dR#VS9dR#VS9dR#\V R24h)TFNz cannot be cast to bool)r)sfalse_values_unionrtrue_values_unions&r! map_string:BooleanArray._from_sequence_of_strings..map_stringls9%%((k! A3&=!>??r$rQ)r6rx) _TRUE_VALUESunion _FALSE_VALUESr'rOrr listmap_from_sequence) rrr6rxrrrrscalarsrfrrs &&$$$$d @@r!_from_sequence_of_strings&BooleanArray._from_sequence_of_strings[s ,,22;3D3D"E ..44\5G5GRH  K @ @((7&1G}c*ten=>!!'T!BBr$c$V^8dQhRRRRRR/#)rr6rrxr5rryr)r s"r!r"r~s$11&1.21 &1r$c <V'd VR8XgQh\WR7#)rr)r)rvaluer6rxs&&$$r!_coerce_to_arrayBooleanArray._coerce_to_array}s  I% %%u00r$c >VPR 9gQh\P!V4pRp\V\4'dVP VP rAM\V4'd@\P!VRR7pVP^8d\#\VRR7wrM0\V\P4'dVP4pV'dSV\P Jd?\P"!V4'g#\%R\'V4P R24hV'g%\)V4\)V48wd \+R4hVPR 9d0\,P.!VP WP V4wrTMnVPR 9d0\,P0!VP WP V4wrTM.\,P2!VP WP V4wrTVP5WT4#) or_Nr5rQFrz+'other' should be pandas.NA or a bool. Got z instead.zLengths must match>rxorand_ror_rxorrand_>rr>rr)rnr is_scalarrXr;rrr r'rndimNotImplementedrr(item libmissingNAis_boolrWrrZrr kleene_or kleene_and kleene_xor_maybe_mask_result)r*otheropother_is_scalarrfrs&&& r!_logical_methodBooleanArray._logical_methods{{MMMM--. e\ * *++u{{4 % JJuF3EzzA~%%)%e>$**eZZNLFD>>$**eZZNLF&&v44r$r|Tc$V^8dQhRRRRRR/#)rrr.r|r5rrr)r s"r!r"rs$$( r$c VPpVPpVR9d/\\V4pV!WE3RV/VBwrEVP WE4#^RIHpV!VP\4V4P!V3RV/VB#)cumminr|) IntegerArray)rcummax) rrgetattrrrpandas.core.arraysrrint _accumulate)r*rr|kwargsrgrfrrs&&$, r!rBooleanArray._accumulateszzzz ' '-t4BD@v@@JD##D/ / 7 C 0$7CC#'- r$r>1TRUETruetrue1.0>0FALSEFalsefalse0.0)F)rnrorprqrrrr classmethodrrrur6rr'rnumbersNumberr5r(_HANDLED_TYPESrrrrv __classcell__)rs@r!r;r;s8t8L;M 2 2C  C )- C*.C)-CC>jj'..$AN15:11!5F+/r$r;)NF)& __future__rrtypingrrrrnumpyr' pandas._libsrr rpandas.util._decoratorsr pandas.core.dtypes.commonr pandas.core.dtypes.dtypesr pandas.core.dtypes.missingr pandas.corerpandas.core.array_algosrpandas.core.arrays.maskedrrrTpandas._typingrrrrrrr;rr$r!rs"/2>+8  9 HC;?C;C;LRj On?nnr$