+ ŜiRt^RIHt^RIHtHtHt^RIt^RI H t ^RI H t H t ^RIHtHtHt^RIHt^RIHt^R IHt^R IHtHt^R IHt]'d%^R IHt^R IH t ^RIH!t!^RI"H#t#H$t$^RI%H&t&H't'H(t(]RRRll4t)]RRRll4t)]RRRll4t)]!R4RRRll4t)R RRllt*R!RRllt+R#)"z timedelta support tools ) annotations) TYPE_CHECKINGAnyoverloadN)lib)NaTNaTType) Timedeltadisallow_ambiguous_unitparse_timedelta_unit) set_module) is_list_like) ArrowDtype)ABCIndex ABCSeries)sequence_to_td64ns)Hashable) timedelta) UnitChoices) ArrayLikeDateTimeErrorChoices)IndexSeriesTimedeltaIndexc(V^8dQhRRRRRRRR/#) argzstr | float | timedeltaunitUnitChoices | Noneerrorsrreturnr )formats"e/Users/mibo/.openclaw/workspace/.venv-ak/lib/python3.14/site-packages/pandas/core/tools/timedeltas.py __annotate__r$6s0   ! cR#Nr!rrrs&&&r# to_timedeltar)5s r%c(V^8dQhRRRRRRRR/#)rrrrrrrr r!)r"s"r#r$r$>s0   ! r%cR#r'r!r(s&&&r#r)r)=s r%c(V^8dQhRRRRRRRR/#) rrz(list | tuple | range | ArrayLike | Indexrrrrr rr!)r"s"r#r$r$Fs0 1  ! r%cR#r'r!r(s&&&r#r)r)Es r%pandasc(V^8dQhRRRRRRRR/#) rrzQstr | int | float | timedelta | list | tuple | range | ArrayLike | Index | Seriesrrrrr z3Timedelta | TimedeltaIndex | Series | NaTType | Anyr!)r"s"r#r$r$Ns@AKAK AK AK !AK9AKr%cVe\V4p\V4VR9d \R4hVf\#\ V\ 4'd?\ VPWR7pVPW0PVPR7#\ V\4'd\ WW PR7#\ V\P4'd)VP^8Xd\P !V4pMM\#V4'd \%VR^4^8Xd\ WVR7#\%VR^4^8d \'R4h\ V\(4'dVe \R4h\+WVR7#) a, Convert argument to timedelta. Timedeltas are absolute differences in times, expressed in difference units (e.g. days, hours, minutes, seconds). This method converts an argument from a recognized timedelta format / value into a Timedelta type. Parameters ---------- arg : str, timedelta, list-like or Series The data to be converted to timedelta. .. versionchanged:: 2.0 Strings with units 'M', 'Y' and 'y' do not represent unambiguous timedelta values and will raise an exception. unit : str, optional Denotes the unit of the arg for numeric `arg`. Defaults to ``"ns"``. Possible values: * 'W' * 'D' / 'days' / 'day' * 'hours' / 'hour' / 'hr' / 'h' * 'm' / 'minute' / 'min' / 'minutes' * 's' / 'seconds' / 'sec' / 'second' * 'ms' / 'milliseconds' / 'millisecond' / 'milli' / 'millis' * 'us' / 'microseconds' / 'microsecond' / 'micro' / 'micros' * 'ns' / 'nanoseconds' / 'nano' / 'nanos' / 'nanosecond' Must not be specified when `arg` contains strings and ``errors="raise"``. errors : {'raise', 'coerce'}, default 'raise' - If 'raise', then invalid parsing will raise an exception. - If 'coerce', then invalid parsing will be set as NaT. Returns ------- timedelta If parsing succeeded. Return type depends on input: - list-like: TimedeltaIndex of timedelta64 dtype - Series: Series of timedelta64 dtype - scalar: Timedelta See Also -------- DataFrame.astype : Cast argument to a specified dtype. to_datetime : Convert argument to datetime. convert_dtypes : Convert dtypes. Notes ----- If the precision is higher than nanoseconds, the precision of the duration is truncated to nanoseconds for string inputs. Examples -------- Parsing a single string to a Timedelta: >>> pd.to_timedelta("1 days 06:05:01.00003") Timedelta('1 days 06:05:01.000030') >>> pd.to_timedelta("15.5us") Timedelta('0 days 00:00:00.000015500') Parsing a list or array of strings: >>> pd.to_timedelta(["1 days 06:05:01.00003", "15.5us", "nan"]) TimedeltaIndex(['1 days 06:05:01.000030', '0 days 00:00:00.000015500', NaT], dtype='timedelta64[ns]', freq=None) Converting numbers by specifying the `unit` keyword argument: >>> pd.to_timedelta(np.arange(5), unit="s") TimedeltaIndex(['0 days 00:00:00', '0 days 00:00:01', '0 days 00:00:02', '0 days 00:00:03', '0 days 00:00:04'], dtype='timedelta64[s]', freq=None) >>> pd.to_timedelta(np.arange(5), unit="D") TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[s]', freq=None) z+errors must be one of 'raise', or 'coerce'.)rr)indexname)rrr2ndimzBarg must be a string, timedelta, list, tuple, 1-d array, or Seriesz9unit must not be specified if the input is/contains a str)raisecoerce)r r ValueErrorr isinstancer_convert_listlike_values _constructorr1r2rnpndarrayr3ritem_from_zerodimr getattr TypeErrorstr _coerce_scalar_to_timedelta_type)rrrvaluess&&& r#r)r)Ms:D #D)% ((FGG { C # #"3;;TIiichhGG C " " XXNN C $ $Q ##C( c  wsFA6!; ?? fa 1 $ P  #s 0TUU ,C6 JJr%c$V^8dQhRRRRRR/#)rrrrrr zTimedelta | NaTTyper!)r"s"r#r$r$s$ 0Dr%c^\W4pV# \dTR8Xdh\pT#i;i)z)Convert string 'r' to a timedelta object.r4)r r6r)rrrresults&&& r#rArAs> 1# M  W   M s ,,c$V^8dQhRRRRRR/#)rrrrrr2zHashable | Noner!)r"s"r#r$r$s(  !  r%cx\VRR4p\V\\34'gVf\P !V\ R7pM)\V\4'dVPR8XdV#\WVRR7^,p^RI H pWPJ;'g\P!W4pV!WSVR7pV#) z6Convert a list of objects to a timedelta index object.dtypeN)rImF)rrcopy)r)r2rK) r>r7listtupler;arrayobjectrkindrr.rmay_share_memory) rrrr2 arg_dtypetd64arrrrKvalues &&&& r#r8r8sWd+I#e}%%):hhs&) Iz * *y~~/D  UKANG% > > >R00>D 7D 9E Lr%)..)Nr4)nsr4)Nr4N),__doc__ __future__rtypingrrrnumpyr; pandas._libsrpandas._libs.tslibsrrpandas._libs.tslibs.timedeltasr r r pandas.util._decoratorsr pandas.core.dtypes.commonr pandas.core.dtypes.dtypesrpandas.core.dtypes.genericrrpandas.core.arrays.timedeltasrcollections.abcrdatetimerrpandas._typingrrr.rrrr)rAr8r!r%r#res#  /20 =(":        HAKAKH"r%