IjpSrSSKJr SSKJrJr SSKJrJrJ r J r J r J r SSK rSSKJrJr SSKJrJrJrJrJrJrJr SSKJr SS KJr SS KJ r J!r!J"r"J#r# SS K$J%r% SS K&J'r'J(r( SS K)J*r* SSK+J,r,J-r- SSK.J/r/J0r0J1r1J2r2 SSK3J4s J5r6 SSK7J4s J8s J9r: SSK7J;r; SSKJ?r? SSK@JArA \(aSSKBJCrC SSKDJDrD SSKEJFrFJGrGJHrHJIrI SSKJJKrK \L"\:R5rM"SS\=\5rN"SS\N\5rOg)z; Base and utility classes for tseries type pandas objects. ) annotations)ABCabstractmethod) TYPE_CHECKINGAnyLiteralSelfcastfinalN)NaTlib) BaseOffset ResolutionTick Timedelta Timestampparsing to_offset)abbrev_to_npy_unit)function)InvalidIndexErrorNullFrequencyErrorOutOfBoundsDatetimeOutOfBoundsTimedelta)cache_readonly) is_integer is_list_like) concat_compat)CategoricalDtype PeriodDtype) DatetimeArrayExtensionArray PeriodArrayTimedeltaArray)Index)NDArrayBackedExtensionIndex) RangeIndex) to_timedelta)Sequence)datetime)AxisJoinHowTimeUnitnpt)CategoricalIndexc^\rSrSr%SrSrS\S'SSS.S$S jjr\S%S j5r \ RS&S j5r \S'S j5r \S(S j5r \ \S)Sj55r\ S(Sj5r\ S*Sj5rS+SjrS,SjrU4SjrSrSS.S-Sjjr\S5rU4SjrS.S(U4Sjjjr\S/Sj5rS0SjrS1SjrS2Sjr\S3Sj5rS4S jr S5S6S!jjr!S"r"S#r#U=r$$)7DatetimeIndexOpsMixinXzE Common ops mixin to support a unified interface datetimelike Index. Fz,DatetimeArray | TimedeltaArray | PeriodArray_dataTrskipnaaxisc4URRXS9$)a Return the mean value of the Array. Parameters ---------- skipna : bool, default True Whether to ignore any NaT elements. axis : int, optional, default 0 Axis for the function to be applied on. Returns ------- scalar Timestamp or Timedelta. See Also -------- numpy.ndarray.mean : Returns the average of array elements along a given axis. Series.mean : Return the mean value in a Series. Notes ----- mean is only defined for Datetime and Timedelta dtypes, not for Period. Examples -------- For :class:`pandas.DatetimeIndex`: >>> idx = pd.date_range("2001-01-01 00:00", periods=3) >>> idx DatetimeIndex(['2001-01-01', '2001-01-02', '2001-01-03'], dtype='datetime64[us]', freq='D') >>> idx.mean() Timestamp('2001-01-02 00:00:00') For :class:`pandas.TimedeltaIndex`: >>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit="D") >>> tdelta_idx TimedeltaIndex(['1 days', '2 days', '3 days'], dtype='timedelta64[s]', freq=None) >>> tdelta_idx.mean() Timedelta('2 days 00:00:00') r4)r3mean)selfr5r6s q/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/pandas/core/indexes/datetimelike.pyr8DatetimeIndexOpsMixin.mean`sZzzf88c.URR$)a Return the frequency object if it is set, otherwise None. To learn more about the frequency strings, please see :ref:`this link`. See Also -------- DatetimeIndex.freq : Return the frequency object if it is set, otherwise None. PeriodIndex.freq : Return the frequency object if it is set, otherwise None. Examples -------- >>> datetimeindex = pd.date_range( ... "2022-02-22 02:22:22", periods=10, tz="America/Chicago", freq="h" ... ) >>> datetimeindex DatetimeIndex(['2022-02-22 02:22:22-06:00', '2022-02-22 03:22:22-06:00', '2022-02-22 04:22:22-06:00', '2022-02-22 05:22:22-06:00', '2022-02-22 06:22:22-06:00', '2022-02-22 07:22:22-06:00', '2022-02-22 08:22:22-06:00', '2022-02-22 09:22:22-06:00', '2022-02-22 10:22:22-06:00', '2022-02-22 11:22:22-06:00'], dtype='datetime64[us, America/Chicago]', freq='h') >>> datetimeindex.freq r3freqr9s r:r?DatetimeIndexOpsMixin.freqs8zzr<c$XRlgNr>)r9values r:r?rAs  r<c.URR$rC)r3asi8r@s r:rFDatetimeIndexOpsMixin.asi8zzr<cSSKJn URRbL[ UR[ U45(a+[ URR5RnU$URR$)a^ Return the frequency object as a string if it's set, otherwise None. See Also -------- DatetimeIndex.inferred_freq : Returns a string representing a frequency generated by infer_freq. Examples -------- For DatetimeIndex: >>> idx = pd.DatetimeIndex(["1/1/2020 10:00:00+00:00"], freq="D") >>> idx.freqstr 'D' The frequency can be inferred if there are more than 2 points: >>> idx = pd.DatetimeIndex( ... ["2018-01-01", "2018-01-03", "2018-01-05"], freq="infer" ... ) >>> idx.freqstr '2D' For PeriodIndex: >>> idx = pd.PeriodIndex(["2023-1", "2023-2", "2023-3"], freq="M") >>> idx.freqstr 'M' r) PeriodIndex) pandasrJr3freqstr isinstancer#r r?_freqstr)r9rJr?s r:rLDatetimeIndexOpsMixin.freqstrsa@ ' ::   )j JJk2/ / tzz/88DK::%% %r<cgrCr@s r:_resolution_obj%DatetimeIndexOpsMixin._resolution_objs-0r<c.URR$)z? Returns day, hour, minute, second, millisecond or microsecond )r3 resolutionr@s r:rU DatetimeIndexOpsMixin.resolutions zz$$$r<c.URR$rC)r3_hasnar@s r:hasnansDatetimeIndexOpsMixin.hasnansszz   r<cnURU5(ag[U[5(dgURRS;ag[U[ U55(dSnUR RnUR[:XaURU;nOD[UR[5(a%[SU5nURRU;nU(a[ U5"U5n[ U5[ U5:wagURUR:Xa+[ R""UR$UR$5$URRS:XaUR&UR&:XdURRS:Xa]UR R)UR 5upE[ R""UR+S5UR+S55$g![[[4a gf=f![,[.4a gf=f)z< Determines if two Index objects contain the same elements. TFiufcr/Mmi8)is_rMr%dtypekindtyper3_infer_matchesobject inferred_typerr categories ValueError TypeError OverflowErrornp array_equalrFtz_ensure_matching_resosviewrr)r9other should_try inferableleftrights r:equalsDatetimeIndexOpsMixin.equalss 88E??%'' [[   'E4:..J 11I{{f$"00I= EKK)9::/7"--;;yH ! Ju-E :e $ ZZ5;; &>>$))UZZ8 8jjoo$EHH)<TWAW I"jj?? L ~~diiouzz$7GHH)#I}=! ! ! ()=>  s$+H)'H!HH!H43H4c~[U5 URU5 g![[[[ 4a gf=f)a Return a boolean indicating whether the provided key is in the index. Parameters ---------- key : label The key to check if it is present in the index. Returns ------- bool Whether the key search is in the index. Raises ------ TypeError If the key is not hashable. See Also -------- Index.isin : Returns an ndarray of boolean dtype indicating whether the list-like key is in the index. Examples -------- >>> idx = pd.Index([1, 2, 3, 4]) >>> idx Index([1, 2, 3, 4], dtype='int64') >>> 2 in idx True >>> 6 in idx False FT)hashget_locKeyErrorrirhr)r9keys r: __contains__"DatetimeIndexOpsMixin.__contains__s@D S   LL )Z1BC  s <<c|>[R"[U5R55n[TU]X5$rC)rkasarrayr(to_numpysuper_convert_tolerance)r9 tolerancetarget __class__s r:r(DatetimeIndexOpsMixin._convert_toleranceGs/JJ|I6??AB w))<[TU]5nURH8nUS:XdM URnUb [ U5nUR SU45 M: U$)z8 Return a list of tuples of the (attr,formatted_value). r?)r _format_attrs _attributesrLreprappend)r9attrsattribr?rs r:r#DatetimeIndexOpsMixin._format_attrs\sY%'&&F||#:D fd^, ' r<ch>[TU]US9nUR(aUSUR3- nU$)z Return a summarized representation. Parameters ---------- name : str name to use in the summary representation Returns ------- String with a summarized representation of the index namez Freq: )r_summaryr?rL)r9rresultrs r:rDatetimeIndexOpsMixin._summaryjs8!t!, 99 / /F r<cXR:$rC)rR)r9resos r:_can_partial_date_slice-DatetimeIndexOpsMixin._can_partial_date_slices****r<c[erCNotImplementedError)r9rparseds r:_parsed_string_to_bounds.DatetimeIndexOpsMixin._parsed_string_to_boundss!!r<c URb[URS5(a URnWb"[ U[ 5(d UR nOUn[ U[R5(a [ U5n[R"X5upE[R"U5nXF4$![a [US[USS55nNf=f)N rule_coderL inferred_freq) r?hasattrrgetattrrMstrrrkstr_rparse_datetime_string_with_resor from_attrname)r9labelr?rLrreso_strrs r:_parse_with_reso&DatetimeIndexOpsMixin._parse_with_resos Ryy GDII{$C$Cyy  JtS$9$9nnGG eRWW % %JE"BB5R''1|# R4GD/4,PQD Rs4B88"CCcURU5up#URX25$![an[U5UeSnAff=frC)r_partial_date_slicerz)r9r{rrerrs r:_get_string_slice'DatetimeIndexOpsMixin._get_string_slicesF,,S1  )++D9 9 )3-S ( )s& A <AcURU5(d[eURX5up4URRnURR nUR (am[U5(a&X0S:aX@S:dX0S:aX@S:a[eURU"U5SS9nURU"U5SS9n[Xx5$XV"U5:n XV"U5:*n X-R5S$)zc Parameters ---------- reso : Resolution parsed : datetime Returns ------- slice or ndarray[intp] rrssidert) rrhrr3_ndarray_unboxis_monotonic_increasinglenrz searchsortedslicenonzero) r9rrt1t2valsunboxrsrtlhs_maskrhs_masks r:r)DatetimeIndexOpsMixin._partial_date_slices ++D11 ..t<zz"" !!  ' '4yy1g"Aw,BbMbPR8m $$U2YV$E% %uRy(HuRy(H'00215 5r<cR[U[5(a2URU5up4UR WW5upgUS:XaU$U$[XR R5(dUR SU5 U$![anUR SX5 SnANwSnAff=f)z If label is a string, cast it to scalar type according to resolution. Parameters ---------- label : object side : {'left', 'right'} Returns ------- label : object Notes ----- Value of `side` parameter should be validated in caller. rNrs)rMrrrh_raise_invalid_indexerrr3_recognized_scalars)r9rrrrrloweruppers r:_maybe_cast_slice_bound-DatetimeIndexOpsMixin._maybe_cast_slice_bounds" eS ! ! A#44U;  88vFLE FN5 5 5E::#A#ABB  ' ' 7  A++GU@@  AsB B& B!!B&c[e)a Shift index by desired number of time frequency increments. This method is for shifting the values of datetime-like indexes by a specified time increment a given number of times. Parameters ---------- periods : int, default 1 Number of periods (or increments) to shift by, can be positive or negative. freq : pandas.DateOffset, pandas.Timedelta or string, optional Frequency increment to shift by. If None, the index is shifted by its own `freq` attribute. Offset aliases are valid strings, e.g., 'D', 'W', 'M' etc. Returns ------- pandas.DatetimeIndex Shifted index. See Also -------- Index.shift : Shift values of Index. PeriodIndex.shift : Shift values of PeriodIndex. r)r9periodsr?s r:shiftDatetimeIndexOpsMixin.shifts 6"!r<cURRUSS9n[X"RS9$![[4a2 [ U[ 5(d[ R"U5nNPUnNTf=f)zD Analogue to maybe_cast_indexer for get_indexer instead of get_loc. T) allow_objectra) r3_validate_listlikerhrirMr"comasarray_tuplesafer%ra)r9keyarrress r:_maybe_cast_listlike_indexer2DatetimeIndexOpsMixin._maybe_cast_listlike_indexersk **//T/JCS **I& fn55++F3  s/;A1,A10A1rQ)r5boolr6z int | None)returnzBaseOffset | None)rNone)rznpt.NDArray[np.int64])rr)rrrr)rprrr)r{rrr)r list[str]rrr str | NonerrrC)rrrr)rr)rrrztuple[datetime, Resolution])r{rrslice | npt.NDArray[np.intp])rrrr*rr)rrNrintrr )%__name__ __module__ __qualname____firstlineno____doc___can_hold_strings__annotations__r8propertyr?setterrFrLrrrRrUrYrur|r_default_na_reprrrrr rrrrrrrr__static_attributes__ __classcell__rs@r:r1r1Xs 77%)a-9^: [[  '&'&R00%%!!+Z'R= OLP " ,/ >H  '' , + + ",) )6)6)6 & )6 )6VH"> + +r<r1c^\rSrSr%SrS\S'SS/rSS/r\Rr \Rr \Rr\S#Sj5rS$SjrS r\S%S j5rS&S'S jjr\S(S j5r\S)S j5rS*SjrS+SjrS+SjrS+SjrS,S-SjjrSrS.SjrS.SjrS/S0Sjjr U4Sjr!Sr"S1U4Sjjr#S%Sjr$S2Sjr%S3S4U4Sjjjr&S5Sjr'S6Sjr(S+U4Sjjr)S6U4S jjr*S7S8S!jjr+S"r,U=r-$)9DatetimeTimedeltaMixini'zY Mixin class for methods shared by DatetimeIndex and TimedeltaIndex, but not PeriodIndex zDatetimeArray | TimedeltaArrayr3rr?c.URR$rC)r3unitr@s r:rDatetimeTimedeltaMixin.unit6rHr<c|URRU5n[U5RX RS9$)a Convert to a dtype with the given unit resolution. This method is for converting the dtype of a ``DatetimeIndex`` or ``TimedeltaIndex`` to a new dtype with the given unit resolution/precision. Parameters ---------- unit : {'s', 'ms', 'us', 'ns'} Returns ------- same type as self Converted to the specified unit. See Also -------- Timestamp.as_unit : Convert to the given unit. Timedelta.as_unit : Convert to the given unit. DatetimeIndex.as_unit : Convert to the given unit. TimedeltaIndex.as_unit : Convert to the given unit. Examples -------- For :class:`pandas.DatetimeIndex`: >>> idx = pd.DatetimeIndex(["2020-01-02 01:02:03.004005006"]) >>> idx DatetimeIndex(['2020-01-02 01:02:03.004005006'], dtype='datetime64[ns]', freq=None) >>> idx.as_unit("s") DatetimeIndex(['2020-01-02 01:02:03'], dtype='datetime64[s]', freq=None) For :class:`pandas.TimedeltaIndex`: >>> tdelta_idx = pd.to_timedelta(["1 day 3 min 2 us 42 ns"]) >>> tdelta_idx TimedeltaIndex(['1 days 00:03:00.000002042'], dtype='timedelta64[ns]', freq=None) >>> tdelta_idx.as_unit("s") TimedeltaIndex(['1 days 00:03:00'], dtype='timedelta64[s]', freq=None) r)r3as_unitrc _simple_newr)r9rarrs r:rDatetimeTimedeltaMixin.as_unit:s5Xjj  &Dz%%c %::r<c|URRU5n[U5RX RS9$)Nr)r3 _with_freqrcr_name)r9r?rs r:r!DatetimeTimedeltaMixin._with_freqis2jj##D)Dz%%c %;;r<ctURRnUR5nSURlU$)NF)r3rroflags writeable)r9datas r:valuesDatetimeTimedeltaMixin.valuesms/zz""yy{$  r<cUb7X R:wa([U[5(a [U5nX-nX-$US:Xd[ U5S:XaUR 5$URc [ S5eUSXR--nUSXR--nURRXESURURS9n[U5RX`RS9$)a Shift index by desired number of time frequency increments. This method is for shifting the values of datetime-like indexes by a specified time increment a given number of times. Parameters ---------- periods : int, default 1 Number of periods (or increments) to shift by, can be positive or negative. freq : pandas.DateOffset, pandas.Timedelta or string, optional Frequency increment to shift by. If None, the index is shifted by its own `freq` attribute. Offset aliases are valid strings, e.g., 'D', 'W', 'M' etc. Returns ------- pandas.DatetimeIndex Shifted index. See Also -------- Index.shift : Shift values of Index. PeriodIndex.shift : Shift values of PeriodIndex. NrzCannot shift with no freqr)startendrr?rr) r?rMrrrcopyrr3_generate_rangerrcrr)r9rr?offsetrrrs r:rDatetimeTimedeltaMixin.shiftus4   1$$$ ^F= a<3t9>99;  99 $%@A AQ'II--2h99,, ++$TYYTYY, Dz%%f99%==r<c.URR$)a Return the inferred frequency of the index. Returns ------- str or None A string representing a frequency generated by ``infer_freq``. Returns ``None`` if the frequency cannot be inferred. See Also -------- DatetimeIndex.freqstr : Return the frequency object as a string if it's set, otherwise ``None``. Examples -------- For ``DatetimeIndex``: >>> idx = pd.DatetimeIndex(["2018-01-01", "2018-01-03", "2018-01-05"]) >>> idx.inferred_freq '2D' For ``TimedeltaIndex``: >>> tdelta_idx = pd.to_timedelta(["0 days", "10 days", "20 days"]) >>> tdelta_idx TimedeltaIndex(['0 days', '10 days', '20 days'], dtype='timedelta64[us]', freq=None) >>> tdelta_idx.inferred_freq '10D' )r3rr@s r:r$DatetimeTimedeltaMixin.inferred_freqsBzz'''r<c[[UR5n[U5R UR 5R n[USR USR U-U5n[U5$Nrr) r rr?rrr_valueranger')r9r?tickrngs r:_as_range_index&DatetimeTimedeltaMixin._as_range_indexs_D$))$&&tyy188DGNNDHOOd$:DA#r<cx[UR[5=(a [UR[5$rC)rMr?rr9rps r:_can_range_setop'DatetimeTimedeltaMixin._can_range_setops#$))T*Kz%**d/KKr<cSn[U5(d URnOU[U[5(a@[ [ UR URS9RUR55nURRURRR5n[UR5RUURUS9n[!SUR#X55$)N)r)rar?r )rr?rMr'rrsteprrrror3rrarcrr _wrap_setop_result)r9rpres_i8new_freq res_valuesrs r:_wrap_range_setop(DatetimeTimedeltaMixin._wrap_range_setops6{{yyH  + + &++DII6>>tyyIH]]'' (;(;(A(AB djj!-- ** . FD33EBCCr<crURnURnURXBS9nURX5$Nsort)r intersectionr+r9rpr0rsrtr(s r:_range_intersect'DatetimeTimedeltaMixin._range_intersects<##%%""5"4%%e44r<crURnURnURXBS9nURX5$r.)runionr+r2s r: _range_union#DatetimeTimedeltaMixin._range_unions9##%%E-%%e44r<c>[SU5nURU5(aURXS9$URU5(dF[R "XUS9nUR X5nURS5RS5$URX5$)zO intersection specialized to the case with matching dtypes and both non-empty. rr/Ninfer) r r#r3_can_fast_intersectr% _intersectionr'r_fast_intersect)r9rpr0rs r:r<$DatetimeTimedeltaMixin._intersections-u5   ' '(((: :''..((4@F ,,U;F$$T*55g> >''4 4r<cUSUS::aXpCOXpC[USUS5nUSnXV:aUSSnU$[URXe56nURUnU$r)minr slice_locs_values) r9rpr0rsrtrrrlslices r:r=&DatetimeTimedeltaMixin._fast_intersectsz 7eAh %%$r(E"I&a ;"1XF  DOOE78F\\&)F r<cURcgURUR:wagUR(dgURRS:H$)NFr)r?rnr"s r:r;*DatetimeTimedeltaMixin._can_fast_intersect,sC 99  ZZ499 $-- yy{{ar<cURnUbX!R:wagUR(dg[U5S:Xd[U5S:XagUSUS::aXpCOXpCUSnUSnXVU-:H=(d XS;$)NFrTr)r?rr)r9rpr?rsrt right_startleft_ends r:_can_fast_union&DatetimeTimedeltaMixin._can_fast_union>syy <4::-++ t9>SZ1_ 7eAh %%Ah 8$.F;3FFr<c:USUS::aXpCOhUSLaaXpCUSnURUSS9nURSUn[URU45n[U5R XR S9n U $XpCUSn USn X:aURU SS9nURUSn[URU/5n[ U[UR55(deURUR:Xde[U5R U5n U $U$)NrFrsrrrrt) rrBrrcrrrMr3_freqr?) r9rpr0rsrt left_startloc right_chunkdatesrrJ right_ends r: _fast_union"DatetimeTimedeltaMixin._fast_union\s3 7eAh % U]%aJ$$Zf$=C---K!4<<"=>E$Z++E +BFM%8"I   $$XG$EeT$**%566 66;;$))+ ++$Z++E2FMKr<cH>[U[U55(deURUR:XdeURU5(aUR XS9$UR U5(aUR XS9nU$[TU]!X5RS5$)Nr/r:) rMrcrar#r7rKrTr_unionr)r9rpr0rrs r:rWDatetimeTimedeltaMixin._unions%d,,,,zzU[[(((   ' '$$U$6 6    & &%%e%7FM7>%.99'B Br<cNSnURU5(a URnU$)z; Get the freq to attach to the result of a join operation. N)rKr?)r9rpr?s r:_get_join_freq%DatetimeTimedeltaMixin._get_join_freqs(    & &99D r<c>URUR:XdURUR45e[TU] XX4U5upcnURU5URlXcU4$rC)rar_wrap_join_resultrZr3rN)r9joinedrplidxridxhow join_indexrs r:r](DatetimeTimedeltaMixin._wrap_join_resultsn{{djj(C5;; *CC(!&!: 4s"  $"&!4!4U!; %%r<cLURRRS5$)Nr_)r3rror@s r:_get_engine_target)DatetimeTimedeltaMixin._get_engine_targetszz""''--r<cURURRR5nURR U5$rC)ror3rra_from_backing_data)r9rs r:_from_join_target(DatetimeTimedeltaMixin._from_join_targets5TZZ00667zz,,V44r<c~>UR(a[U[[45(a[ UR 5[ UR 5:aVUS:XaUR UR 5nO4URUR 5R UR 5n[TU]%X5$)Nrt) rrMrrrrrceilr_searchsorted_monotonic)r9rrrs r:rm.DatetimeTimedeltaMixin._searchsorted_monotonics  ( (59i"899"5::.1CDII1NNw dii0 499-55dii@w.u;;r<cSnURb[U5(a.US[U5*S[U5S- 4;a URnU$[U5(aA[R "[ R"U[ RS9[U55n[U[5(aGURS;a7URS;dUR[U5S4;a URnU$)z' Find the `freq` for self.delete(loc). Nrrrrr)rN)r?rrrr maybe_indices_to_slicerkrintprMrr&rstop)r9rPr?s r:_get_delete_freq'DatetimeTimedeltaMixin._get_delete_freqs 99 #1s4yj"c$i!m<<99D  $$44 3bgg6D Cc5))chh).CyyI-c$i=N1N#yy r<cJURRU5nURRU5nSnURbUR(asU[ LaU$US[ U5*4;a#X R-US:XaURnU$U[ U5:Xa!X R- US:Xa URnU$[UR[5(aURnU$URRU5(a URnU$)z- Find the `freq` for self.insert(loc, item). Nrr) r3_validate_scalar _box_funcr?sizer rrMr is_on_offset)r9rPitemrDr?s r:_get_insert_freq'DatetimeTimedeltaMixin._get_insert_freqs ++D1zz##E* 99 yy3; QT O+yy0@DG0K99D SY&D99,<R,H99D DIIt,,yy ''--yy r<cf>[TU]U5nURU5URlU$)aA Make new Index with passed location(-s) deleted. Parameters ---------- loc : int or list of int Location of item(-s) which will be deleted. Use a list of locations to delete more than one value at the same time. Returns ------- Index Will be same type as self, except for RangeIndex. See Also -------- numpy.delete : Delete any rows and column from NumPy array (ndarray). Examples -------- >>> idx = pd.Index(["a", "b", "c"]) >>> idx.delete(1) Index(['a', 'c'], dtype='str') >>> idx = pd.Index(["a", "b", "c"]) >>> idx.delete([0, 2]) Index(['b'], dtype='str') )rdeletersr3rN)r9rPrrs r:r~DatetimeTimedeltaMixin.deletes/8$!2237  r<c>[TU]X5n[U[U55(a UR X5UR lU$)ae Make new Index inserting new item at location. Follows Python numpy.insert semantics for negative values. Parameters ---------- loc : int The integer location where the new item will be inserted. item : object The new item to be inserted into the Index. Returns ------- Index Returns a new Index object resulting from inserting the specified item at the specified location within the original Index. See Also -------- Index.append : Append a collection of Indexes together. Examples -------- >>> idx = pd.Index(["a", "b", "c"]) >>> idx.insert(1, "x") Index(['a', 'x', 'b', 'c'], dtype='str') )rinsertrMrcr{r3rN)r9rPrzrrs r:rDatetimeTimedeltaMixin.inserts@8* fd4j ) )!%!6!6s!AFLL  r<c l[R"SU5 [R"U[RS9n[ R "XX#U40UD6n[R"U[U55n[U[5(a+URRU5nXRlU$)a Return a new Index of the values selected by the indices. For internal compatibility with numpy arrays. Parameters ---------- indices : array-like Indices to be taken. axis : {0 or 'index'}, optional The axis over which to select values, always 0 or 'index'. allow_fill : bool, default True How to handle negative values in `indices`. * False: negative values in `indices` indicate positional indices from the right (the default). This is similar to :func:`numpy.take`. * True: negative values in `indices` indicate missing values. These values are set to `fill_value`. Any other other negative values raise a ``ValueError``. fill_value : scalar, default None If allow_fill=True and fill_value is not None, indices specified by -1 are regarded as NA. If Index doesn't hold NA, raise ValueError. **kwargs Required for compatibility with numpy. Returns ------- Index An index formed of elements at the given indices. Will be the same type as self, except for RangeIndex. See Also -------- numpy.ndarray.take: Return an array formed from the elements of a at the given indices. Examples -------- >>> idx = pd.Index(["a", "b", "c"]) >>> idx.take([2, 2, 1, 2]) Index(['c', 'c', 'b', 'c'], dtype='str') rQr)nv validate_takerkrrqr&taker rprrMrr3_get_getitem_freqrN) r9indicesr6 allow_fill fill_valuekwargsr maybe_slicer?s r:rDatetimeTimedeltaMixin.take>sb V$**WBGG4,11 4Z ;A 00#d)D k5 ) )::// d ( (JLD4555.( $G<$LC& &* & * &  & O &.5 <<&,4@ P << < <<r<r)Pr __future__rabcrrtypingrrrr r r numpyrk pandas._libsr r pandas._libs.tslibsrrrrrrrpandas._libs.tslibs.dtypesrpandas.compat.numpyrr pandas.errorsrrrrpandas.util._decoratorsrpandas.core.dtypes.commonrrpandas.core.dtypes.concatrpandas.core.dtypes.dtypesrr pandas.core.arraysr!r"r#r$pandas.core.commoncorecommonrpandas.core.indexes.baseindexesbaseibaser%pandas.core.indexes.extensionr&pandas.core.indexes.ranger'pandas.core.tools.timedeltasr(collections.abcr)r*pandas._typingr+r,r-r.rKr/dict_index_doc_kwargsr1rrQr<r:rs#:. 4  ! ((F05(!(001L+7L+^S 2CS r<