+ xȇi3Rt^RIHt^RIHtHt^RIHtH t ^RI H t H t H t ^RIHt^RIHt^RIHtHt^RIHt^R IHt^R IHt^R IHuHt^R IH t H!t!^R I"H#t#^RI$H%t%]'d^RIH&t&^RI H't'H(t(^RI)H*t*H+t+]%!.RO]PXO]RR7]%!.RO]4]!R4!RR]#4444t-]!R4RRR /RRlll4t.R #)zimplement the TimedeltaIndex) annotations) TYPE_CHECKINGcast)indexlib) Resolution Timedelta to_offset)abbrev_to_npy_unit) set_module) is_scalar pandas_dtype) ArrowDtype) ABCSeries)TimedeltaArrayN)Indexmaybe_extract_name)DatetimeTimedeltaMixin) inherit_names)NaTType)DayTick)DtypeObjTimeUnitT)wrappandasc]tRt^2t$RtRt]t]RRl4t R] R&] Pt ]RRl4t R ]PR R R 3R R lltR R ltRtRRltRRlt]RRl4tRtR #)TimedeltaIndexa0 Immutable Index of timedelta64 data. Represented internally as int64, and scalars returned Timedelta objects. Parameters ---------- data : array-like (1-dimensional), optional Optional timedelta-like data to construct index with. freq : str or pandas offset object, optional One of pandas date offset strings or corresponding objects. The string ``'infer'`` can be passed in order to set the frequency of the index as the inferred frequency upon creation. dtype : numpy.dtype or str, default None Valid ``numpy`` dtypes are ``timedelta64[ns]``, ``timedelta64[us]``, ``timedelta64[ms]``, and ``timedelta64[s]``. 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 : object Name to be stored in the index. Attributes ---------- days seconds microseconds nanoseconds components inferred_freq Methods ------- to_pytimedelta to_series round floor ceil to_frame mean See Also -------- Index : The base pandas Index type. Timedelta : Represents a duration between two dates or times. DatetimeIndex : Index of datetime64 data. PeriodIndex : Index of Period data. timedelta_range : Create a fixed-frequency TimedeltaIndex. Notes ----- To learn more about the frequency strings, please see :ref:`this link`. Examples -------- >>> pd.TimedeltaIndex(["0 days", "1 days", "2 days", "3 days", "4 days"]) TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[us]', freq=None) We can also let pandas infer the frequency when possible. >>> pd.TimedeltaIndex(np.arange(5) * 24 * 3600 * 1e9, freq="infer") TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq='D') timedeltaindexcV^8dQhRR/#)returnztype[libindex.TimedeltaEngine])formats"n/Users/max/.openclaw/workspace/postharvest/venv/lib/python3.14/site-packages/pandas/core/indexes/timedeltas.py __annotate__TimedeltaIndex.__annotate__s((<(c "\P#N)libindexTimedeltaEngineselfs&r$ _engine_typeTimedeltaIndex._engine_types'''r'r_datacV^8dQhRR/#)r r!zResolution | Noner")r#s"r$r%r&s**!2*r'c .VPP#r))r0_resolution_objr,s&r$r3TimedeltaIndex._resolution_objszz)))r'NcV^8dQhRR/#)r copyz bool | Noner")r#s"r$r%r&s0<0<  0  ~r'cV^8dQhRR/#)r r!r_r")r#s"r$r%r&ssr'c R#) timedelta64r"r,s&r$ inferred_typeTimedeltaIndex.inferred_typesr'r")__name__ __module__ __qualname____firstlineno____doc___typr _data_clspropertyr.__annotations__r_get_string_slicer3rrArIrQrYrerort__static_attributes__r"r'r$rr2s4EN DI (( //** ^^  0`. Examples -------- >>> pd.timedelta_range(start="1 day", periods=4) TimedeltaIndex(['1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[us]', freq='D') The ``closed`` parameter specifies which endpoint is included. The default behavior is to include both endpoints. >>> pd.timedelta_range(start="1 day", periods=4, closed="right") TimedeltaIndex(['2 days', '3 days', '4 days'], dtype='timedelta64[us]', freq='D') The ``freq`` parameter specifies the frequency of the TimedeltaIndex. Only fixed frequencies can be passed, non-fixed frequencies such as 'M' (month end) will raise. >>> pd.timedelta_range(start="1 day", end="2 days", freq="6h") TimedeltaIndex(['1 days 00:00:00', '1 days 06:00:00', '1 days 12:00:00', '1 days 18:00:00', '2 days 00:00:00'], dtype='timedelta64[us]', freq='6h') Specify ``start``, ``end``, and ``periods``; the frequency is generated automatically (linearly spaced). >>> pd.timedelta_range(start="1 day", end="5 days", periods=4) TimedeltaIndex(['1 days 00:00:00', '2 days 08:00:00', '3 days 16:00:00', '5 days 00:00:00'], dtype='timedelta64[us]', freq=None) **Specify a unit** >>> pd.timedelta_range("1 Day", periods=3, freq="100000D", unit="s") TimedeltaIndex(['1 days', '100001 days', '200001 days'], dtype='timedelta64[s]', freq='100000D') DzVOf the four parameters: start, end, periods, and freq, exactly three must be specifiedrz Tick | Day)closedr;r8)comany_noner count_not_none ValueErrorrrr r;_cresobasefreqstrr_generate_rangerrB) startendrr:r9rr;cresorHs &&&&&&$ r$timedelta_rangers~ | WS99 T?D %g49 8   |  e$EC.CE*Ey#&C!%**-0B3880LLJ 3J1  e$EE*E EJJ/DC.Cy#&C CHH-D   d+D&t,E{{U"J (9(9:  * * G& E  % %e % 77r')__neg____pos____abs__ total_secondsrjfloorceil) componentsto_pytimedeltasumstdmedian)NNNNNN)/rz __future__rtypingrr pandas._libsrr*rpandas._libs.tslibsrrr pandas._libs.tslibs.dtypesr pandas.util._decoratorsr pandas.core.dtypes.commonr r pandas.core.dtypes.dtypesrpandas.core.dtypes.genericrpandas.core.arrays.timedeltasrpandas.core.commoncorecommonrpandas.core.indexes.baserr pandas.core.indexes.datetimelikerpandas.core.indexes.extensionrrrrpandas._typingrr _field_opsrrr"r'r$rs""  :.108 D7$    " "     HI+I  2IX HI8!I8I8r'