*jpdZddlmZddlmZmZddlmZmZm Z m Z m Z m Z ddl ZddlmZmZddlmZmZmZmZmZmZmZddlmZdd lmZdd lm Z m!Z!m"Z"m#Z#dd l$m%Z%dd l&m'Z'm(Z(dd l)m*Z*ddl+m,Z,m-Z-ddl.m/Z/m0Z0m1Z1m2Z2ddl3m4cm5Z6ddl7m4cm8cm9Z:ddl7m;Z;ddlm?Z?ddl@mAZAerddlBmCZCddlDmDZDddlEmFZFmGZGmHZHmIZIddlJmKZKeLe:jZMGdde=eZNGddeNeZOy)z; Base and utility classes for tseries type pandas objects. ) annotations)ABCabstractmethod) TYPE_CHECKINGAnyLiteralSelfcastfinalN)NaTlib) BaseOffset ResolutionTick Timedelta Timestampparsing to_offset)abbrev_to_npy_unit)function)InvalidIndexErrorNullFrequencyErrorOutOfBoundsDatetimeOutOfBoundsTimedelta)cache_readonly) is_integer is_list_like) concat_compat)CategoricalDtype PeriodDtype) DatetimeArrayExtensionArray PeriodArrayTimedeltaArray)Index)NDArrayBackedExtensionIndex) RangeIndex) to_timedelta)Sequence)datetime)AxisJoinHowTimeUnitnpt)CategoricalIndexceZdZUdZdZded<dddd"dZed#d Zejd$d Zed%d Z ed&d Z e e d'd Ze d&dZe d(dZd)dZd*dZfdZdZdd d+dZedZfdZd,d&fd Zed-dZd.dZd/dZd0dZe d1dZd2dZd3d4d Z d!Z!xZ"S)5DatetimeIndexOpsMixinzM Common ops mixin to support a unified interface datetimelike Index. Fz,DatetimeArray | TimedeltaArray | PeriodArray_dataTrskipnaaxisc<|jj||S)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') r3)r2mean)selfr4r5s BC:\FundamentalWorkbench\vendor\pandas\core\indexes\datetimelike.pyr7zDatetimeIndexOpsMixin.mean`sZzzf488c.|jjS)ac 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 r2freqr8s r9r=zDatetimeIndexOpsMixin.freqs8zzr:c&||j_yNr<)r8values r9r=zDatetimeIndexOpsMixin.freqs  r:c.|jjSr@)r2asi8r>s r9rCzDatetimeIndexOpsMixin.asi8zzr:cddlm}|jjGt |jt |fr+t |jjj}|S|jjS)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) pandasrFr2freqstr isinstancer#r r=_freqstr)r8rFr=s r9rHzDatetimeIndexOpsMixin.freqstrs\@ ' ::   )j JJk2/ tzz/88DK::%% %r:cyr@r>s r9_resolution_objz%DatetimeIndexOpsMixin._resolution_objs-0r:c.|jjS)zO Returns day, hour, minute, second, millisecond or microsecond )r2 resolutionr>s r9rOz DatetimeIndexOpsMixin.resolutions zz$$$r:c.|jjSr@)r2_hasnar>s r9hasnanszDatetimeIndexOpsMixin.hasnansszz   r:c"|j|ryt|tsy|jjdvryt|t |sd}|j j}|jtk(r|j|v}n>t|jtr$td|}|jj|v}|r t ||}t |t |k7ry|j|jk(r*t!j"|j$|j$S|jjdk(r|j&|j&k(s|jjdk(r] |j j)|j \}}t!j"|j+d|j+dSy#tttf$rYywxYw#t,t.f$rYywxYw)zL Determines if two Index objects contain the same elements. TFiufcr/Mmi8)is_rIr%dtypekindtyper2_infer_matchesobject inferred_typerr categories ValueError TypeError OverflowErrornp array_equalrCtz_ensure_matching_resosviewrr)r8other should_try inferableleftrights r9equalszDatetimeIndexOpsMixin.equalss 88E?%' [[   'E4:.J 11I{{f$"00I= EKK)9:/7"--;;yH !&DJu-E :e $ ZZ5;; &>>$))UZZ8 8jjoo$EHH)<TWAW I"jj?? L e~~diiouzz$7GHH)#I}=! ! ! ()=>  s$ G"(G<"G98G9<H Hc|t| |j|y#tttt f$rYywxYw)a Return a boolean indicating whether the provided key is in the index. Parameters ---------- key : label The key to check if it is present in the index. Returns ------- bool Whether the key search is in the index. Raises ------ TypeError If the key is not hashable. See Also -------- Index.isin : Returns an ndarray of boolean dtype indicating whether the list-like key is in the index. Examples -------- >>> idx = pd.Index([1, 2, 3, 4]) >>> idx Index([1, 2, 3, 4], dtype='int64') >>> 2 in idx True >>> 6 in idx False FT)hashget_locKeyErrorrar`r)r8keys r9 __contains__z"DatetimeIndexOpsMixin.__contains__s@D S   LL )Z1BC  s ;;c|tjt|j}t|||Sr@)rcasarrayr(to_numpysuper_convert_tolerance)r8 tolerancetarget __class__s r9rxz(DatetimeIndexOpsMixin._convert_toleranceGs1JJ|I6??AB w))V<s r9_formatter_funcz%DatetimeIndexOpsMixin._formatter_funcXszz$$&&r:ct|}|jD]4}|dk(s |j}| t |}|j d|f6|S)zH Return a list of tuples of the (attr,formatted_value). r=)rw _format_attrs _attributesrHreprappend)r8attrsattribr=r{s r9rz#DatetimeIndexOpsMixin._format_attrs\sY%'&&F||#:D fd^, ' r:cdt||}|jr|d|jz }|S)a 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: )rw_summaryr=rH)r8rresultr{s r9rzDatetimeIndexOpsMixin._summaryjs8!t!, 99 / /F r:c ||jkDSr@)rM)r8resos r9_can_partial_date_slicez-DatetimeIndexOpsMixin._can_partial_date_slicesd****r:ctr@NotImplementedError)r8rparseds r9_parsed_string_to_boundsz.DatetimeIndexOpsMixin._parsed_string_to_boundss!!r:c  |jt|jdr |j}t |t s |j }n|}t |tjr t |}tj||\}}tj|}||fS#t$rt|dt|dd}YwxYw)N rule_coderH inferred_freq) r=hasattrrgetattrrIstrrrcstr_rparse_datetime_string_with_resor from_attrname)r8labelr=rHrreso_strrs r9_parse_with_resoz&DatetimeIndexOpsMixin._parse_with_resos Ryy GDII{$Cyy  JtS$9nnGG eRWW %JE"BB5'R''1t|# R4GD/4,PQD Rs.B((!C  C c|j|\}} |j||S#t$r}t||d}~wwxYwr@)r_partial_date_slicerq)r8rrrrerrs r9_get_string_slicez'DatetimeIndexOpsMixin._get_string_slicesJ,,S1  )++D&9 9 )3-S ( )s( A =Ac|j|st|j||\}}|jj}|jj }|j rot|r&||dkr||dks||dkDr||dkDrt|j||d}|j||d}t||S|||k\} |||k} | | zjdS)z Parameters ---------- reso : Resolution parsed : datetime Returns ------- slice or ndarray[intp] rrksiderl) rr`rr2_ndarray_unboxis_monotonic_increasinglenrq searchsortedslicenonzero) r8rrt1t2valsunboxrkrllhs_maskrhs_masks r9rz)DatetimeIndexOpsMixin._partial_date_slices ++D1 ..tV<Bzz"" !!  ' '4yd1g"tAw,BbMb4PR8m $$U2YV$Eu% %uRy(HuRy(Hx'00215 5r:cBt|tr3 |j|\}}|j \}}|dk(r|S|St||j js|j d||S#t$r}|j d||Yd}~sd}~wwxYw)aL 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. rNrk)rIrrr`_raise_invalid_indexerrr2_recognized_scalars)r8rrrrrloweruppers r9_maybe_cast_slice_boundz-DatetimeIndexOpsMixin._maybe_cast_slice_bounds" eS ! A#44U;  88vFLE5 FN5 5 5E4::#A#AB  ' ' 7  A++GUC@@  AsA88 BBBct)ae 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)r8periodsr=s r9shiftzDatetimeIndexOpsMixin.shifts 6"!r:c |jj|d}t||jS#ttf$r+t |t st j|}n|}YPwxYw)zT Analogue to maybe_cast_indexer for get_indexer instead of get_loc. T) allow_objectrY) r2_validate_listliker`rarIr"comasarray_tuplesafer%rY)r8keyarrress r9_maybe_cast_listlike_indexerz2DatetimeIndexOpsMixin._maybe_cast_listlike_indexersk **//T/JCS **I& fn5++F3  s67A0/A0)r4boolr5z int | None)returnzBaseOffset | None)rNone)rznpt.NDArray[np.int64])rr)rrrr)rhrrr)rrrrr)r list[str]r~rr| str | Nonerrr@)rrrr)rr)rrrztuple[datetime, Resolution])rrrrslice | npt.NDArray[np.intp])rrrr*rr)rrNrintrr )#__name__ __module__ __qualname____doc___can_hold_strings__annotations__r7propertyr=setterrCrHrrrMrOrRrmrsrx_default_na_reprrrrr rrrrrrrr __classcell__r{s@r9r1r1Xsz 77%)a-9^: [[  '&'&R00%%!!+Z'R= OLP " ,/ >H  '' , + + ",) )6)6)6 & )6 )6VH"> +r:r1ceZdZUdZded<ddgZddgZejZ ejZ ejZ ed!dZd"dZdZed#d Zd$d%d Zed&d Zed'd Zd(d Zd)dZd)dZd)dZd*d+dZdZd,dZd,dZd-d.dZfdZ dZ! d/fd Z"d#dZ#d0dZ$d1d2fd Z%d3dZ&d4dZ'd)fd Z(d4fd Z) d5 d6d Z*xZ+S)7DatetimeTimedeltaMixinze Mixin class for methods shared by DatetimeIndex and TimedeltaIndex, but not PeriodIndex zDatetimeArray | TimedeltaArrayr2rr=c.|jjSr@)r2unitr>s r9rzDatetimeTimedeltaMixin.unit6rDr:c|jj|}t|j||jS)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)r2as_unitr[ _simple_newr)r8rarrs r9rzDatetimeTimedeltaMixin.as_unit:s7Xjj  &Dz%%c %::r:c|jj|}t|j||jS)Nr)r2 _with_freqr[r_name)r8r=rs r9rz!DatetimeTimedeltaMixin._with_freqis4jj##D)Dz%%c %;;r:ct|jj}|j}d|j_|S)NF)r2rrgflags writeable)r8datas r9valueszDatetimeTimedeltaMixin.valuesms/zz""yy{$  r:c|4||jk7r%t|tr t|}||z}||zS|dk(st |dk(r|j S|j t d|d||jzz}|d||jzz}|jj||d|j|j}t|j||jS)ad 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=rIrrrcopyrr2_generate_rangerr[rr)r8rr=offsetrrrs r9rzDatetimeTimedeltaMixin.shiftus4   1$$ t^F&= a<3t9>99;  99 $%@A AQ'DII--2h499,, ++S$TYYTYY, Dz%%f499%==r:c.|jjS)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' )r2rr>s r9rz$DatetimeTimedeltaMixin.inferred_freqsBzz'''r:ctt|j}t|j |j j }t|dj |dj |z|}t|SNrr) r rr=rrr_valueranger')r8r=tickrngs r9_as_range_indexz&DatetimeTimedeltaMixin._as_range_indexs_D$))$&&tyy188DGNNDHOOd$:DA#r:cnt|jtxrt|jtSr@)rIr=rr8rhs r9_can_range_setopz'DatetimeTimedeltaMixin._can_range_setops#$))T*Kz%**d/KKr:cd}t|s |j}nSt|trCt t |j |jj|j}|jj|jjj}t|jj||j|}t!d|j#||S)N)r)rYr=r )rr=rIr'rrsteprrrrgr2rrYr[rr _wrap_setop_result)r8rhres_i8new_freq res_valuesrs r9_wrap_range_setopz(DatetimeTimedeltaMixin._wrap_range_setops6{yyH  + &++DII6>>tyyIH]]'' (;(;(A(AB djj!-- ** . FD33E6BCCr:c||j}|j}|j||}|j||SNsort)r intersectionr r8rhrrkrlrs r9_range_intersectz'DatetimeTimedeltaMixin._range_intersects@##%%""5t"4%%eV44r:c||j}|j}|j||}|j||Sr )runionr rs r9 _range_unionz#DatetimeTimedeltaMixin._range_unions=##%%E-%%eV44r:c<td|}|j|r|j||S|j|sJt j |||}|j ||}|jdjdS|j||S)z_ intersection specialized to the case with matching dtypes and both non-empty. rr Ninfer) r rr_can_fast_intersectr% _intersectionrr_fast_intersect)r8rhrrs r9rz$DatetimeTimedeltaMixin._intersections-u5   '((T(: :''.((u4@F ,,UF;F$$T*55g> >''t4 4r:c|d|dkr||}}n||}}t|d|d}|d}||kr|dd}|St|j||}|j|}|Sr)minr slice_locs_values) r8rhrrkrlrrrlslices r9rz&DatetimeTimedeltaMixin._fast_intersects 7eAh %D%D$r(E"I&a ;"1XF  DOOE378F\\&)F r:c|jy|j|jk7ry|jsy|jjdk(S)NFr)r=rnrs r9rz*DatetimeTimedeltaMixin._can_fast_intersect,sC 99  ZZ499 $-- yy{{ar:c|j}|||jk7ry|jsyt|dk(st|dk(ry|d|dkr||}}n||}}|d}|d}|||zk(xs||vS)NFrTr)r=rr)r8rhr=rkrl right_startleft_ends r9_can_fast_unionz&DatetimeTimedeltaMixin._can_fast_union>syy <45::-++ t9>SZ1_ 7eAh %D%DAh 8x$.F;$3FFr:cJ|d|dkr||}}nr|durj||}}|d}|j|d}|jd|}t|j|f}t|j ||j } | S||}}|d} |d} | | kr|j| d}|j|d}t|j|g}t |t|jsJ|j|jk(sJt|j |} | S|S)NrFrkrrrrl) rrrr[rrrIr2_freqr=) r8rhrrkrl left_startloc right_chunkdatesrr# right_ends r9 _fast_unionz"DatetimeTimedeltaMixin._fast_union\s@ 7eAh %D U]%DaJ$$Zf$=C---K!4<<"=>E$Z++E +BFM%D8"I  i $$XG$EeT$**%56 66;;$))+ ++$Z++E2FMKr:c:t|t|sJ|j|jk(sJ|j|r|j ||S|j |r|j ||}|St|!||jdS)Nr r) rIr[rYrrr$r,rw_unionr)r8rhrrr{s r9r.zDatetimeTimedeltaMixin._unions%d,,,zzU[[(((   '$$U$6 6    &%%e$%7FM7>%.99'B Br:cDd}|j|r |j}|S)zK Get the freq to attach to the result of a join operation. N)r$r=)r8rhr=s r9_get_join_freqz%DatetimeTimedeltaMixin._get_join_freqs%    &99D r:c|j|jk(sJ|j|jft| |||||\}}}|j||j_|||fSr@)rYrw_wrap_join_resultr0r2r&)r8joinedrhlidxridxhow join_indexr{s r9r2z(DatetimeTimedeltaMixin._wrap_join_resultsv{{djj(C5;; *CC(!&!: E4s"  D$"&!4!4U!; 4%%r:cL|jjjdS)NrW)r2rrgr>s r9_get_engine_targetz)DatetimeTimedeltaMixin._get_engine_targetszz""''--r:c|j|jjj}|jj |Sr@)rgr2rrY_from_backing_data)r8rs r9_from_join_targetz(DatetimeTimedeltaMixin._from_join_targets5TZZ00667zz,,V44r:ch|jrt|ttfrt |j t |j kDrU|dk(r|j |j }n4|j|j j |j }t|%||S)Nrl) rrIrrrrrceilrw_searchsorted_monotonic)r8rrr{s r9r?z.DatetimeTimedeltaMixin._searchsorted_monotonics  ( (59i"89"5::.1CDII1NNw dii0 499-55dii@w.ud;;r:cd}|jt|r,|dt| dt|dz fvr |j}|St|rBt j t j|t jt|}t|trA|jdvr3|jdvs|jt|dfvr |j}|S)z7 Find the `freq` for self.delete(loc). Nrrrrr)rN)r=rrrr maybe_indices_to_slicercruintprIrrrstop)r8r(r=s r9_get_delete_freqz'DatetimeTimedeltaMixin._get_delete_freqs 99 #1s4yj"c$i!m<<99D  $44 3bgg6D Cc5)chh).CyyI-c$i=N1N#yy r:c"|jj|}|jj|}d}|j|jro|t ur |S|dt | fvr#||jz|dk(r|j}|S|t |k(r!||jz |dk(r |j}|St|jtr|j}|S|jj|r |j}|S)z= Find the `freq` for self.insert(loc, item). Nrr) r2_validate_scalar _box_funcr=sizer rrIr is_on_offset)r8r(itemrAr=s r9_get_insert_freqz'DatetimeTimedeltaMixin._get_insert_freqs ++D1zz##E* 99 yy3; QT O+tyy0@DG0K99D SY&D499,<R,H99D DIIt,yy ''-yy r:cft||}|j||j_|S)a 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') )rwdeleterDr2r&)r8r(rr{s r9rMzDatetimeTimedeltaMixin.deletes/8$!2237  r:ct|||}t|t|r!|j |||j _|S)a 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') )rwinsertrIr[rKr2r&)r8r(rJrr{s r9rOzDatetimeTimedeltaMixin.insertsA8T* fd4j )!%!6!6sD!AFLL  r:c ftjd|tj|tj}t j |||||fi|}tj|t|}t|tr,|jj|}||j_|S)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') rLr)nv validate_takercrurBr&taker rArrIrr2_get_getitem_freqr&) r8indicesr5 allow_fill fill_valuekwargsr maybe_slicer=s r9rSzDatetimeTimedeltaMixin.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 numpyrc pandas._libsr r pandas._libs.tslibsrrrrrrrpandas._libs.tslibs.dtypesrpandas.compat.numpyrrQ 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.rGr/dict_index_doc_kwargsr1rrLr:r9r~s#:. 4  ! ((F05(!(001L+7L+^S 2CS r: