Lg[>SSKJrJrJrJrJrJrJrJrJ r J r J r J r J r JrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJ r J!r!J"r"J#r#J$r$J%r%J&r&J'r'J(r(J)r)J*r*J+r+J,r,J-r-J.r.J/r/J0r0J1r1J2r2J3r3J4r4J5r5J6r6J7r7J8r8J9r9J:r:J;r;Jr>J?r?J@r@JArAJBrBJCrCJDrDJErEJFrFJGrGJHrH SSKIJJrJ SSKKrKSSKLJMrM SSKNrNSSKOrPSSKOJQrQ SSKRJSrS SrT\J"SS 5rUS rVS rWS rXS rYSrZSr[Sr\Sr]\]"5 S Sjr^S!SS.Sjjr_SSS.Sjr`SraS"SS.SjjrbS"SS.SjjrcSSSS.SjrdSreSrfg)#)HFunctionFunctionOptionsFunctionRegistryHashAggregateFunctionHashAggregateKernelKernelScalarAggregateFunctionScalarAggregateKernelScalarFunction ScalarKernelVectorFunction VectorKernelArraySortOptionsAssumeTimezoneOptions CastOptions CountOptionsCumulativeOptionsCumulativeSumOptionsDayOfWeekOptionsDictionaryEncodeOptionsRunEndEncodeOptionsElementWiseAggregateOptionsExtractRegexOptions FilterOptions IndexOptions JoinOptionsListSliceOptionsListFlattenOptionsMakeStructOptionsMapLookupOptionsMatchSubstringOptions ModeOptions NullOptions PadOptionsPairwiseOptionsPartitionNthOptionsQuantileOptions RandomOptions RankOptionsReplaceSliceOptionsReplaceSubstringOptionsRoundBinaryOptions RoundOptionsRoundTemporalOptionsRoundToMultipleOptionsScalarAggregateOptionsSelectKOptionsSetLookupOptions SliceOptions SortOptions SplitOptionsSplitPatternOptionsStrftimeOptionsStrptimeOptionsStructFieldOptions TakeOptionsTDigestOptions TrimOptionsUtf8NormalizeOptionsVarianceOptions WeekOptions call_functionfunction_registry get_functionlist_functionscall_tabular_functionregister_scalar_functionregister_tabular_functionregister_aggregate_functionregister_vector_function UdfContext Expression) namedtupleN)dedent)_compute_docstrings) docscrapec.URR$N)_doc arg_names)funcs /lib/python3.12/site-packages/pyarrow/compute.py_get_arg_namesrUks 99  _OptionsClassDoc)paramscUR(dg[R"UR5n[US5$)N Parameters)__doc__rNNumpyDocStringrW) options_classdocs rT_scrape_options_class_docr_rs4    " "=#8#8 9C C - ..rVc ,URn[URURURUR S9UlXlXl/nURnU(d0URS:aSOSnSRURU5nURUS35 URnU(aURUS35 [RRUR5n UR[!S55 [#U5n U H@n UR$S ;aS n OS n URU S U S 35 URS5 MB UGb?['U5n U (agU R(HVnURURS UR*S 35 UR,HnURSUS 35 M MX O[.R0"SURS3[25 [4R6"U5nUR8R;5HAnUR[!SRURUR555 MC UR[!SURS355 UR[!S55 U b8URSR[!U 5R=S 555 SR?U5Ul U$)N)namearityr]options_required argumentsargumentz,Call compute function {!r} with the given {}z. z z. Parameters ---------- )vectorscalar_aggregatez Array-likezArray-like or scalar-likez :  z" Argument to compute function. z zOptions class z does not have a docstringz {0} : optional Parameter for {1} constructor. Either `options` or `{0}` can be passed, but not both at the same time. z& options : pyarrow.compute.zK, optional Alternative way of passing options. z memory_pool : pyarrow.MemoryPool, optional If not passed, will allocate memory from the default memory pool. z {} )!rQdictrarbr]rc__arrow_compute_function____name__ __qualname__summaryformatappend descriptionrMfunction_doc_additionsgetrLrUkindr_rXtypedescwarningswarnRuntimeWarninginspect signature parametersvaluesstripjoinr[)wrapper exposed_namerSr]cpp_doc doc_piecesroarg_strrr doc_additionrRarg_namearg_typeoptions_class_docps options_sigs rT_decorate_compute_functionrysiiG)- YYjj++ 11 *3G& $'JooG !%a+ZAF499g.  '(%%K[M./&==AA$))LLf   t$I 996 6#H2HXJc(267?@  5mD &--!!QVVHCxr":;A%%QCrl3 . MMN=+A+A*BC678F H!++M:K ++224!!&*F166=#9#9: #<=5 &&''4'='=&>? "  f   (//&*>*D*DT*JKLggj)GO NrVcURRnU(dg[5U$![a- [R "SR U5[5 gf=f)Nz!Python binding for {} not exposed)rQr]globalsKeyErrorrxryrprz)rS class_names rT_get_options_classrsV((J y$$  9vj)> ;s -4A$#A$c U(dU(a%Ub[SRU55eU"U0UD6$UbS[U[5(aU"S0UD6$[X!5(aU$[SRX[ U555eg)NzMFunction {!r} called with both an 'options' argument and additional argumentsz-Function {!r} expected a {} parameter, got {}) TypeErrorrp isinstancerkrv)rar]optionsargskwargss rT_handle_optionsrs v  + d-f-- gt $ $ +7+ +  / /N ; VDg 79 9 rVcL^^^^TcSS.UUU4SjjnU$SSS.UUUU4SjjnU$)N memory_poolc >T[La,[U5T:wa[TSTS[U5S35eU(a8[US[5(a [R "T[ U55$TRUSU5$)N takes  positional argument(s), but were givenr)EllipsislenrrrJ_calllistcall)rrrbrS func_names rTr&_make_generic_wrapper..wrappersH$Te); k0t9+[2 47J77!'' 4:>>99T45 5rV)rrc H>T[La7[U5T:a[TSTS[U5S35eUTSnUSTnOSn[TTUXC5nU(a9[ US[ 5(a![ R "T[U5U5$TRX!U5$)Nrrrrr) rrrrrrJrrr) rrrr option_argsrbrSrr]s rTrrsH$t9u$#$+WUG4"4yk6#56l FU| %i&1;G 47J77!'' 4:wGG99TK8 8rVr)rrSr]rbrs```` rT_make_generic_wrapperrs5'+ 6 64 N!(,T 9 9 NrVcSSKJn /nUH$nURU"XSR55 M& UH$nURU"XSR55 M& Ub[R "U5nUR R5H\nURURUR4;deU(aURURS9nURU5 M^ URU"SURSS95 URU"SURSS95 [R"U5$)Nr) Parameter)rur)defaultr) r{rrqPOSITIONAL_ONLYVAR_POSITIONALr|r}r~ruPOSITIONAL_OR_KEYWORD KEYWORD_ONLYreplace Signature)rR var_arg_namesr]rrXrarrs rT_make_signaturer s! F i&?&?@A i&>&>?@ '' 6 ''..0A66i=='4466 66II9#9#9I: MM!  1  i 9+A+A(,. / MM)M9+A+A$(*+   V $$rVc[U5n[U5nU=(a USRS5nU(a!UR5R S5/nO/n[ XX!R S9n[X5U5Ul[X`X5$)N*)rb) rrU startswithpoplstriprrbr __signature__r)rarSr]rR has_varargrrs rT_wrap_functionr#s&t,Mt$I>> from datetime import datetime >>> import pyarrow as pa >>> arr = pa.array([datetime(2010, 1, 1), datetime(2015, 1, 1)]) >>> arr.type TimestampType(timestamp[us]) You can use ``pyarrow.DataType`` objects to specify the target type: >>> cast(arr, pa.timestamp('ms')) [ 2010-01-01 00:00:00.000, 2015-01-01 00:00:00.000 ] >>> cast(arr, pa.timestamp('ms')).type TimestampType(timestamp[ms]) Alternatively, it is also supported to use the string aliases for these types: >>> arr.cast('timestamp[ms]') [ 2010-01-01 00:00:00.000, 2015-01-01 00:00:00.000 ] >>> arr.cast('timestamp[ms]').type TimestampType(timestamp[ms]) Returns ------- casted : Array The cast result as a new Array NzRMust either pass values for 'target_type' and 'safe' or pass a value for 'options'Fcast) ValueErrorpatypeslib ensure_typerunsafesafer@)arr target_typerrrsafe_vars_passeds rTrrSslD(Fk.EW0:; ;hhll..{; 5=!((5G!&&{3G # ==rVrcbUb*UbURX#U- 5nO'URU5nOUbURSU5n[U[R5(d[R"XR S9nOGUR UR :wa-[R"UR 5UR S9n[US9n[SU/XT5nUbMUR 5S:a9[R"UR 5U-[R"5S9nU$)a Find the index of the first occurrence of a given value. Parameters ---------- data : Array-like value : Scalar-like object The value to search for. start : int, optional end : int, optional memory_pool : MemoryPool, optional If not passed, will allocate memory from the default memory pool. Returns ------- index : int the index, or -1 if not found Examples -------- >>> import pyarrow as pa >>> import pyarrow.compute as pc >>> arr = pa.array(["Lorem", "ipsum", "dolor", "sit", "Lorem", "ipsum"]) >>> pc.index(arr, "ipsum") >>> pc.index(arr, "ipsum", start=2) >>> pc.index(arr, "amet") rrvvalueindex) slicerrScalarscalarrvas_pyrr@int64)datarstartendrrresults rTrrs>  ?::e5[1D::e$D zz!S! eRYY ' ' %ii0 ejj  %++-dii8'G 7TFG AF V\\^q06<<>E1 C MrVT) boundscheckrc0[US9n[SX/XC5$)a Select values (or records) from array- or table-like data given integer selection indices. The result will be of the same type(s) as the input, with elements taken from the input array (or record batch / table fields) at the given indices. If an index is null then the corresponding value in the output will be null. Parameters ---------- data : Array, ChunkedArray, RecordBatch, or Table indices : Array, ChunkedArray Must be of integer type boundscheck : boolean, default True Whether to boundscheck the indices. If False and there is an out of bounds index, will likely cause the process to crash. memory_pool : MemoryPool, optional If not passed, will allocate memory from the default memory pool. Returns ------- result : depends on inputs Selected values for the given indices Examples -------- >>> import pyarrow as pa >>> arr = pa.array(["a", "b", "c", None, "e", "f"]) >>> indices = pa.array([0, None, 4, 3]) >>> arr.take(indices) [ "a", null, "e", null ] )rtake)r:r@)rindicesrrrs rTrrs Pk2G $' GGrVcd[U[R[R[R45(d[R "XR S9nOGUR UR :wa-[R "UR5UR S9n[SX/5$)aReplace each null element in values with a corresponding element from fill_value. If fill_value is scalar-like, then every null element in values will be replaced with fill_value. If fill_value is array-like, then the i-th element in values will be replaced with the i-th element in fill_value. The fill_value's type must be the same as that of values, or it must be able to be implicitly casted to the array's type. This is an alias for :func:`coalesce`. Parameters ---------- values : Array, ChunkedArray, or Scalar-like object Each null element is replaced with the corresponding value from fill_value. fill_value : Array, ChunkedArray, or Scalar-like object If not same type as values, will attempt to cast. Returns ------- result : depends on inputs Values with all null elements replaced Examples -------- >>> import pyarrow as pa >>> arr = pa.array([1, 2, None, 3], type=pa.int8()) >>> fill_value = pa.scalar(5, type=pa.int8()) >>> arr.fill_null(fill_value) [ 1, 2, 5, 3 ] >>> arr = pa.array([1, 2, None, 4, None]) >>> arr.fill_null(pa.array([10, 20, 30, 40, 50])) [ 1, 2, 30, 4, 50 ] rcoalesce) rrArray ChunkedArrayrrrvrr@)r~ fill_values rT fill_nullrstf j288R__bii"H I IYYz <   'YYz//1 D f%9 ::rVcUc/n[U[R[R45(aUR S5 O [ SU5n[ X5n[SU/XC5$)a< Select the indices of the top-k ordered elements from array- or table-like data. This is a specialization for :func:`select_k_unstable`. Output is not guaranteed to be stable. Parameters ---------- values : Array, ChunkedArray, RecordBatch, or Table Data to sort and get top indices from. k : int The number of `k` elements to keep. sort_keys : List-like Column key names to order by when input is table-like data. memory_pool : MemoryPool, optional If not passed, will allocate memory from the default memory pool. Returns ------- result : Array Indices of the top-k ordered elements Examples -------- >>> import pyarrow as pa >>> import pyarrow.compute as pc >>> arr = pa.array(["a", "b", "c", None, "e", "f"]) >>> pc.top_k_unstable(arr, k=3) [ 5, 4, 2 ] )dummy descendingc US4$)Nrrkey_names rT top_k_unstable..[s (L)ArVselect_k_unstablerrrrrqmapr1r@r~k sort_keysrrs rTtop_k_unstabler1sbJ &288R__56601A9M Q*G ,vh MMrVcUc/n[U[R[R45(aUR S5 O [ SU5n[ X5n[SU/XC5$)aS Select the indices of the bottom-k ordered elements from array- or table-like data. This is a specialization for :func:`select_k_unstable`. Output is not guaranteed to be stable. Parameters ---------- values : Array, ChunkedArray, RecordBatch, or Table Data to sort and get bottom indices from. k : int The number of `k` elements to keep. sort_keys : List-like Column key names to order by when input is table-like data. memory_pool : MemoryPool, optional If not passed, will allocate memory from the default memory pool. Returns ------- result : Array of indices Indices of the bottom-k ordered elements Examples -------- >>> import pyarrow as pa >>> import pyarrow.compute as pc >>> arr = pa.array(["a", "b", "c", None, "e", "f"]) >>> pc.bottom_k_unstable(arr, k=3) [ 0, 1, 2 ] )r ascendingc US4$)Nrrrs rTr#bottom_k_unstable..s (K)@rVrrrs rTbottom_k_unstabler`sbJ &288R__566/0@)L Q*G ,vh MMrVsystem) initializerrrc,[US9n[S/X#US9$)a Generate numbers in the range [0, 1). Generated values are uniformly-distributed, double-precision in range [0, 1). Algorithm and seed can be changed via RandomOptions. Parameters ---------- n : int Number of values to generate, must be greater than or equal to 0 initializer : int or str How to initialize the underlying random generator. If an integer is given, it is used as a seed. If "system" is given, the random generator is initialized with a system-specific source of (hopefully true) randomness. Other values are invalid. options : pyarrow.compute.RandomOptions, optional Alternative way of passing options. memory_pool : pyarrow.MemoryPool, optional If not passed, will allocate memory from the default memory pool. )rrandom)length)r(r@)nrrrs rTrrs, 4G 2wA FFrVcT[U5nUS:Xa[US[[45(a[R "US5$[US[ 5(a[R"US5$[S[US535e[R"U5$)aReference a column of the dataset. Stores only the field's name. Type and other information is known only when the expression is bound to a dataset having an explicit scheme. Nested references are allowed by passing multiple names or a tuple of names. For example ``('foo', 'bar')`` references the field named "bar" inside the field named "foo". Parameters ---------- *name_or_index : string, multiple strings, tuple or int The name or index of the (possibly nested) field the expression references to. Returns ------- field_expr : Expression Reference to the given field Examples -------- >>> import pyarrow.compute as pc >>> pc.field("a") >>> pc.field(1) >>> pc.field(("a", "b")) >> pc.field("a", "b") r?r@rArBrCrDrErFrGrHrIrJ collectionsrKr{textwraprLrxpyarrowrrMpyarrow.vendoredrNrUrWr_rrrrrrrrrrrrrrrrrrVrTrs7$MMMMMMMMMMMMMMMMMMM^#'&0+>/Pf *>%. J ;:B>J/D/d(,)HX8;v,NT,N^,N,N^&tG4.7b%rV