]jKbSSKJr SSKJrJr SSKJrJr SSKrSSK J r SSK J r JrJrJrJrJr SSKJr SSKJrJrJr SS KJr SS KJr SS KJr SS KJ r SS K!J"r"J#r#J$r$J%r% SSK&J's J(r) SSK*J's J+s J,r- SSK*J.r. SSK/J0r0 SSK1J2r2J3r3 SSK4J5r5 \(aSSK6J7r7 SSK8J9r9J:r:J;r; \<"\-Rz5r=\=R}SS05 SS0r?Sr@\5"SSS/\"RQ\"SS9\5"S/\"5\"S5"S S!\05555rB\"S5S#S$S"jj5rCg)%) annotations)datetime timedelta) TYPE_CHECKINGSelfN)index) BaseOffsetDayNaTPeriod ResolutionTick)OFFSET_TO_PERIOD_FREQSTR)cache_readonlydoc set_module) is_integer) PeriodDtype) ABCSeries)is_valid_na_for_dtype) PeriodArray period_arrayraise_on_incompatiblevalidate_dtype_freq)maybe_extract_name)DatetimeIndexOpsMixin) DatetimeIndexIndex) inherit_names)Hashable)DtypeDtypeObjnpt target_klasszPeriodIndex or list of Periodsklassrc URS5nURS:Xa9URSS5n[U5n[X$S9nUR"U40UD6$U"U40UD6$)Ndataint64freqdtype)popr+rr _simple_new)clsdvaluesr)r+s W/home/mande/repo/quber/.venv/lib/python3.13/site-packages/pandas/core/indexes/period.py_new_PeriodIndexr2Fsc UU6]F ||wuuVT"D!V1v+++6Qstrftime start_timeend_timeT)wrap is_leap_yearpandasc R^\rSrSr%SrSrS\S'S\S'S\S '\rS r \ S(S j5r \ S)S j5r \"\R4S SS.\D6S*S+Sjj5r\"\R"5S,S-Sjj5r\ \"\R$R&5S.Sj55r\ \"\R(R&5S.Sj55r\ \"\R*R&5S.Sj55rS/S0Sjjr\SSSSSSSSS.S1Sjj5r\SS.S1Sjj5r\ S2Sj5rS3SjrS4SjrS5U4Sjjr\ S6Sj5r\ S7Sj5rU4S jr S!r!S8S"jr"S9S#jr#\"\$RJ5S:U4S$jj5r%S;S%jr&\"\$RN5S PeriodIndexRa% Immutable ndarray holding ordinal values indicating regular periods in time. Index keys are boxed to Period objects which carries the metadata (eg, frequency information). Parameters ---------- data : array-like (1d int np.ndarray or PeriodArray), optional Optional period-like data to construct index with. freq : str or period object, optional One of pandas period strings or corresponding objects. dtype : str or PeriodDtype, default None A dtype from which to extract a freq. copy : bool, default None Whether to copy input data, only relevant for array, Series, and Index inputs (for other input, e.g. a list, a new array is created anyway). Defaults to True for array input and False for Index/Series. Set to False to avoid copying array input at your own risk (if you know the input data won't be modified elsewhere). Set to True to force copying Series/Index input up front. name : str, default None Name of the resulting PeriodIndex. Attributes ---------- day dayofweek day_of_week dayofyear day_of_year days_in_month daysinmonth end_time freq freqstr hour is_leap_year minute month quarter qyear second start_time week weekday weekofyear year Methods ------- asfreq strftime to_timestamp from_fields from_ordinals Raises ------ ValueError Passing the parameter data as a list without specifying either freq or dtype will raise a ValueError: "freq not specified and cannot be inferred" See Also -------- Index : The base pandas Index type. Period : Represents a period of time. DatetimeIndex : Index with datetime64 data. TimedeltaIndex : Index of timedelta64 data. period_range : Create a fixed-frequency PeriodIndex. Examples -------- >>> idx = pd.PeriodIndex(data=["2000Q1", "2002Q3"], freq="Q") >>> idx PeriodIndex(['2000Q1', '2002Q3'], dtype='period[Q-DEC]') periodindexr_datar r)rr+Tc"[R$N)libindex PeriodEngineselfs r1 _engine_typePeriodIndex._engine_types$$$r3c.URR$r@)r+_resolution_objrCs r1rHPeriodIndex._resolution_objszz)))r3zarrays.PeriodArray)other other_nameNc|URRX5n[U5RX0RS9$Nname)r>asfreqtyper-rOrDr)howarrs r1rPPeriodIndex.asfreqs4jj*Dz%%c %::r3ctURRX5n[R"X0RS9$rM)r> to_timestamprr-rOrRs r1rWPeriodIndex.to_timestamps+jj%%d0((99==r3cT[URRURSS9$NFrOcopy)rr>hourrOrCs r1r]PeriodIndex.hoursTZZ__4995AAr3cT[URRURSS9$rZ)rr>minuterOrCs r1r`PeriodIndex.minute!TZZ&&TYYUCCr3cT[URRURSS9$rZ)rr>secondrOrCs r1rdPeriodIndex.secondrbr3cSnU(d'[U[[45(a URn[ XQU5n[ X25nUR XU5upU(a1[X5(a!URU:waURU5n[XS9nU(aUR5nURXUS9$)N)r'r))rOrefs) isinstancerr _referencesrr_maybe_copy_array_inputr)rPrr\r-)r.r'r)r+r\rOrgs r1__new__PeriodIndex.__new__s 4%);<<##D!$c2"5/00UC  Jt))dii4.?;;t$D1 99;DtT::r3)yearquartermonthdayr]r`rdr)cUUUUUUUS.n U R5V V s0sH upU cM X_M n n n [R"XS9n URU 5$s sn n f)a  Construct a PeriodIndex from fields (year, month, day, etc.). Parameters ---------- year : int, array, or Series, default None Year for the PeriodIndex. quarter : int, array, or Series, default None Quarter for the PeriodIndex. month : int, array, or Series, default None Month for the PeriodIndex. day : int, array, or Series, default None Day for the PeriodIndex. hour : int, array, or Series, default None Hour for the PeriodIndex. minute : int, array, or Series, default None Minute for the PeriodIndex. second : int, array, or Series, default None Second for the PeriodIndex. freq : str or period object, optional One of pandas period strings or corresponding objects. Returns ------- PeriodIndex See Also -------- PeriodIndex.from_ordinals : Construct a PeriodIndex from ordinals. PeriodIndex.to_timestamp : Cast to DatetimeArray/Index. Examples -------- >>> idx = pd.PeriodIndex.from_fields(year=[2000, 2002], quarter=[1, 3]) >>> idx PeriodIndex(['2000Q1', '2002Q3'], dtype='period[Q-DEC]') )rmrnrorpr]r`rd)fieldsr))itemsr _from_fieldsr-) r.rmrnrorpr]r`rdr)rrkeyvaluerTs r1 from_fieldsPeriodIndex.from_fieldssjf 06||~S~*#*~S&&f@s##Ts AArNc[R"U[RS9n[U5n[R "XS9nUR XSS9$)a Construct a PeriodIndex from ordinals. Parameters ---------- ordinals : array-like of int The period offsets from the proleptic Gregorian epoch. freq : str or period object One of pandas period strings or corresponding objects. name : str, default None Name of the resulting PeriodIndex. Returns ------- PeriodIndex See Also -------- PeriodIndex.from_fields : Construct a PeriodIndex from fields (year, month, day, etc.). PeriodIndex.to_timestamp : Cast to DatetimeArray/Index. Examples -------- >>> idx = pd.PeriodIndex.from_ordinals([-1, 0, 1], freq="Q") >>> idx PeriodIndex(['1969Q4', '1970Q1', '1970Q2'], dtype='period[Q-DEC]') r*rN)npasarrayr(rrr-)r.ordinalsr)rOr+r's r1 from_ordinalsPeriodIndex.from_ordinalsAsC<::hbhh7D!&&x=t//r3c4[R"U[S9$)Nr*)rzr{objectrCs r1r0PeriodIndex.valuesgszz$f--r3c[U[[R[[R 45(aC[UR [[45(aURRU5nU$Oy[U[5(a;URUR R:Xa UR$[X5e[U5(a[U[5(deU$[US5e)ae Convert timedelta-like input to an integer multiple of self.freq Parameters ---------- other : timedelta, np.timedelta64, DateOffset, int, np.ndarray Returns ------- converted : int, np.ndarray[int64] Raises ------ IncompatibleFrequency : if the input cannot be written as a multiple of self.freq. Note IncompatibleFrequency subclasses ValueError. N)rhrrz timedelta64rndarrayr)r r> _check_timedeltalike_freq_compatr basenrrint)rDrJdeltas r1_maybe_convert_timedelta$PeriodIndex._maybe_convert_timedeltaks" eirzzJ K K$))dC[11 CCEJ 2z * *zzTYY^^+ww'4 4   eS)) ))L$D$//r3c URU:H$)z6 Can we compare values of the given dtype to our own? r*)rDr+s r1_is_comparable_dtype PeriodIndex._is_comparable_dtypeszzU""r3c>[U[5(a [URURSS9nO [U[5(d [ S5e[ TU]X5$)za where : array of timestamps mask : np.ndarray[bool] Array of booleans where data is not NA. F)r)r\z6asof_locs `where` must be DatetimeIndex or PeriodIndex)rhrr;_valuesr) TypeErrorsuper asof_locs)rDwheremask __class__s r1rPeriodIndex.asof_locssQ e] + + DIIEJEE;//TU Uw --r3c[U5S:XagUR(d [S5eURn[ USSUSS- S:R 55$)zq Returns True if this PeriodIndex is range-like in that all Periods between start and end are present, in order. rTzIndex is not monotonicN)lenis_monotonic_increasing ValueErrorasi8boolall)rDr0s r1is_fullPeriodIndex.is_fullsZ t9>++56 6fQRj6#2;.!388:;;r3cg)NperiodrCs r1 inferred_typePeriodIndex.inferred_typesr3c|>[TU]X5nURUR:XaURU5nU$r@)r_convert_tolerancer+r)rD tolerancetargetrs r1rPeriodIndex._convert_tolerances: G.yA :: %55i@Ir3cUnURU5 [XR5(a[nO[ U[ 5(ahUR U5up4URU5(aURXC5$X@R:XaURU5nOd[U5e[ U[5(aURU5 O2[ U[5(aURU5nO [U5e[ R""X5$![an[SUS35UeSnAff=f![an[U5UeSnAff=f![an[U5UeSnAff=f)aC Get integer location for requested label. Parameters ---------- key : Period, NaT, str, or datetime String or datetime key must be parsable as Period. Returns ------- loc : int or ndarray[int64] Raises ------ KeyError Key is not present in the index. TypeError If key is listlike or otherwise not hashable. zCannot interpret 'z ' as periodN)_check_indexing_errorrr+r rhstr_parse_with_resorKeyError_can_partial_date_slice_partial_date_slicerH_cast_partial_indexing_scalarr _disallow_mismatched_indexingrrget_loc)rDruorig_keyparsedresoerrs r1rPeriodIndex.get_locsa( ""3' jj 1 1C S ! ! O#44S9  ++D11133DAA+++88@sm# V $ $  . .s 3 X & &44S9C3-  .==+ +9 O!3C5 DE3N O 1"3-S01, .8$# - .sH D"5E E"" E,D<<E E EE" E=, E88E=cNURUR:wa [U5egr@)_dtyper+r)rDrus r1r)PeriodIndex._disallow_mismatched_indexings! :: #3-  $r3cj[XRS9nU$![an[U5UeSnAff=f)Nr))r r)rr)rDlabelrrs r1r)PeriodIndex._cast_partial_indexing_scalars: +E 2F  +5/s * +s 2 -2cn>[U[5(aURU5n[TU]X5$r@)rhrrr_maybe_cast_slice_bound)rDrsiders r1r#PeriodIndex._maybe_cast_slice_bounds0 eX & &66u=Ew.u;;r3c[R"URUR5n[X#S9nUR UR SS9UR UR SS94$)Nrstart)rSend)rget attr_abbrevr rPr))rDrrr)ivs r1_parsed_string_to_bounds$PeriodIndex._parsed_string_to_boundssW'++D,<,N>NO F & $)) 1299TYYE93RSSr3cTUb"[S[U5RS35eX-$)Nz%`freq` argument is not supported for z.shift)rrQ__name__)rDperiodsr)s r1shiftPeriodIndex.shifts6  7T 8K8K7LFS ~r3r)returnztype[libindex.PeriodEngine])rr )NE)rSrrr)Nr)rSrrr)rrNNNNN)r+z Dtype | Noner\z bool | NonerOHashable | Nonerr)rr)rznpt.NDArray[np.object_])rzint | npt.NDArray[np.int64])r+r"rr)rrrznpt.NDArray[np.bool_]rz np.ndarray)rr)rr)rur rNone)rrrr )rr)rr rr)rN)rrrr)*r __module__ __qualname____firstlineno____doc___typ__annotations__r _data_cls!_supports_partial_string_indexingpropertyrErrHrrP_shared_doc_kwargsrWr]fgetr`rdrk classmethodrwr}r0rrrrrrrrrrrrr__static_attributes__ __classcell__)rs@r1r;r;RsnL\ D   I(,% %%** "    ;  ;  ! !">#>    B B   !D"D   !D"D " $ !; !;  !;  !; !;F   <$ <$<$|37 0 0J.. 0D# . < < <.|   6 67<8< T   $ $%&r3r;c[R"XU5S:wa [S5eUc,[U[5(d[U[5(dSn[ R "XX#5upS[U5n[ XVS9n[XTSS9$)a- Return a fixed frequency PeriodIndex. The day (calendar) is the default frequency. Parameters ---------- start : str, datetime, date, pandas.Timestamp, or period-like, default None Left bound for generating periods. end : str, datetime, date, pandas.Timestamp, or period-like, default None Right bound for generating periods. periods : int, default None Number of periods to generate. freq : str or DateOffset, optional Frequency alias. By default the freq is taken from `start` or `end` if those are Period objects. Otherwise, the default is ``"D"`` for daily frequency. name : str, default None Name of the resulting PeriodIndex. Returns ------- PeriodIndex A PeriodIndex of fixed frequency periods. See Also -------- date_range : Returns a fixed frequency DatetimeIndex. Period : Represents a period of time. PeriodIndex : Immutable ndarray holding ordinal values indicating regular periods in time. Notes ----- Of the three parameters: ``start``, ``end``, and ``periods``, exactly two must be specified. To learn more about the frequency strings, please see :ref:`this link`. Examples -------- >>> pd.period_range(start="2017-01-01", end="2018-01-01", freq="M") PeriodIndex(['2017-01', '2017-02', '2017-03', '2017-04', '2017-05', '2017-06', '2017-07', '2017-08', '2017-09', '2017-10', '2017-11', '2017-12', '2018-01'], dtype='period[M]') If ``start`` or ``end`` are ``Period`` objects, they will be used as anchor endpoints for a ``PeriodIndex`` with frequency matching that of the ``period_range`` constructor. >>> pd.period_range( ... start=pd.Period("2017Q1", freq="Q"), ... end=pd.Period("2017Q2", freq="Q"), ... freq="M", ... ) PeriodIndex(['2017-03', '2017-04', '2017-05', '2017-06'], dtype='period[M]') rzOOf the three parameters: start, end, and periods, exactly two must be specifiedDr*Fr[) comcount_not_nonerrhr r_generate_rangerr;)rrrr)rOr'r+s r1 period_ranger%sH %g.!3 ,   |Zv66z#v?V?V,,UGJD  E t )D tU 33r3r)rz int | NonerOrrr;)D __future__rrrtypingrrnumpyrz pandas._libsrrApandas._libs.tslibsr r r r r rpandas._libs.tslibs.dtypesrpandas.util._decoratorsrrrpandas.core.dtypes.commonrpandas.core.dtypes.dtypesrpandas.core.dtypes.genericrpandas.core.dtypes.missingrpandas.core.arrays.periodrrrrpandas.core.commoncorecommonrpandas.core.indexes.baseindexesribaser pandas.core.indexes.datetimelikerpandas.core.indexes.datetimesrrpandas.core.indexes.extensionrcollections.abcr pandas._typingr!r"r#dict_index_doc_kwargsupdaterr2 _field_opsr;rrr3r1r s_" *@ 110< ! 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