MhD4SSKJr SSKJrJr SSKrSSKJr SSK J r SSK J r SSK Jr SSKJr SSKrSS KJrJr SS KJr SS KJrJr SS KJrJrJrJr SS KJ r J!r!J"r" \(aSSKJ#r# \RH\RJ\RL\RN\RP\RR\RRS.r*\RL\RVS4\RR\RX\ 4\RH\RZS4\RJ\RZS4\RN\RZS4\R\\RXS4\RP\R^S40r0\RZS\RVS\RXS0r1"SS\5r2g)) annotations) TYPE_CHECKINGAnyN) infer_dtype)iNaT)NoBufferPresent)cache_readonly)BaseMaskedDtype) ArrowDtypeDatetimeTZDtype)is_string_dtype) PandasBufferPandasBufferPyarrow)Column ColumnBuffersColumnNullType DtypeKind) ArrowCTypes Endiannessdtype_to_arrow_c_fmt)Buffer)iufbUMmzThis column is non-nullablezThis column uses NaN as nullz!This column uses a sentinel valuec\rSrSrSrSSSjjrSSjr\SSj5r\ SSj5r SSjr \S5r \S 5r \ SS j5r\SS j5rSS jrSSSjjrSSjrSSjrSSjrSSjrSrg ) PandasColumnHa A column object, with only the methods and properties required by the interchange protocol defined. A column can contain one or more chunks. Each chunk can contain up to three buffers - a data buffer, a mask buffer (depending on null representation), and an offsets buffer (if variable-size binary; e.g., variable-length strings). Note: this Column object can only be produced by ``__dataframe__``, so doesn't need its own version or ``__column__`` protocol. c[U[R5(a[SURS35e[U[R 5(d[ S[U5S35eXlX l g)z] Note: doesn't deal with extension arrays yet, just assume a regular Series/ndarray for now. zExpected a Series, got a DataFrame. This likely happened because you called __dataframe__ on a DataFrame which, after converting column names to string, resulted in duplicated names: zD. 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N Data type z& not supported by interchange protocolz bool[pyarrow]rA) _NP_KINDSgetkind ValueErrorr%r numpy_dtype byteorderr baser itemsizerBOOLr)r/rBrRrUs r2rF$PandasColumn._dtype_from_pandasdtypes}}UZZ. <z%0VWX X eZ ( ())33I  / / ,,I  / /))33II O #    ^^a')=e)DiOOr5cURS[R:Xd [S5eURR R S[[R"URR R55S.$)a If the dtype is categorical, there are two options: - There are only values in the data buffer. - There is a separate non-categorical Column encoding for categorical values. Raises TypeError if the dtype is not categorical Content of returned dict: - "is_ordered" : bool, whether the ordering of dictionary indices is semantically meaningful. - "is_dictionary" : bool, whether a dictionary-style mapping of categorical values to other objects exists - "categories" : Column representing the (implicit) mapping of indices to category values (e.g. an array of cat1, cat2, ...). None if not a dictionary-style categorical. rzCdescribe_categorical only works on a column with categorical dtype!T) is_ordered is_dictionary categories) rBrrGr(r-catorderedr!r&r*r]r8s r2describe_categorical!PandasColumn.describe_categoricalsi$zz!} 5 55U  ))--//!&ryy1I1I'JK  r5c [URR[5(a[R nSnX4$[URR[ 5(acURRRRSR5Sc[RS4$[RS4$URSn[UupEXE4$![a [SUS35ef=f)NrrOz not yet supported)r%r-rBr r USE_BYTEMASKr array _pa_arraychunksbuffers NON_NULLABLE USE_BITMASK_NULL_DESCRIPTIONKeyErrorr+)r/column_null_dtype null_valuerRnullvalues r2 describe_nullPandasColumn.describe_nulls diioo 7 7 . ; ; J$0 0 diiooz 2 2yy((//2::D#D!# q$/48"IINN54<8$:J:J9 JsBBcUR5SSS.nUR5US'UR5US'U$![a N"f=f![a U$f=f)a Return a dictionary containing the underlying buffers. 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Raises NoBufferPresent if null representation is not a bit or byte mask. rrcNrrAshaperBz! so does not have a separate maskzSee self.describe_null)rqr%r-rBr rerfrgrrXrrrHrhrrr _maskrrIrrzerosbool_ enumerater_NO_VALIDITY_BUFFERrlr+r) r/roinvalidrrBrmaskrvalidrrmsgs r2r!PandasColumn._get_validity_bufferns **  diiooz 2 2))//++2215C^^Q (8(8*:K:KLE{{}Q'( a 3xF= diioo 7 799??((D!$'F^^Q (8(8*:K:KLE= ::a=I,, ,))$$&CqLEiG883s8+RXX>D#C.#-c3#7#7%W) "$'F^^Q (8(8*:K:KLE=  @(.//PQC c""  @%&>? ? @s : II'cURS[R:XaURR 5nSn[ R "[U5S-4[ RS9n[U5H>upE[U[5(aURSS9nU[U5- nX#US-'M@ [U5n[RS[R ["R$4nXx4$['S5e)z Return the buffer containing the offset values for variable-size binary data (e.g., variable-length strings) and the buffer's associated dtype. 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E} "5 r5)r.r-)T)r0z pd.Seriesr1boolreturnNone)rint)rztuple[DtypeKind, int, str, str])rzdict[str, pd.Index])N)rz int | None)rr)rz.tuple[Buffer, tuple[DtypeKind, int, str, str]])rztuple[Buffer, Any] | None)rztuple[PandasBuffer, Any])__name__ __module__ __qualname____firstlineno____doc__r3r7propertyr<r rBrFr`rqrwr{r~rrrrr__static_attributes__r;r5r2r!r!Hs &( 77:PB  8&-- 11  "#J< 7<|7#r&r5r!)3 __future__rtypingrrnumpyrpandas._libs.librpandas._libs.tslibsr pandas.errorsrpandas.util._decoratorsr pandas.core.dtypes.dtypesr pandasr&r r pandas.api.typesr pandas.core.interchange.bufferrr*pandas.core.interchange.dataframe_protocolrrrrpandas.core.interchange.utilsrrrrrrrrXrIrrPUSE_NAN USE_SENTINELrirGrdrkrr!r;r5r2rsi" ($)25-  A               OOn,,d3 44d; MMN//6 NN^00$7 NN^00$7N77< ~22A6 !>:!DE6Er5