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„CˆCŒCC”C˜CœC C¤C¨C¬C°C´C¸C ¼C!ÀC"ÄC#ÈC$ÌC&ÐC'ÔC(ØC)ÜC+àC,äC-èC.ìC/ðC0ôC1øC2üC4D5D6D7D8D:D;D<D= D@$DA(DB,DC0DE4DF8DG<DK@DLDDMHDOLDRPDSTDTXDU\DX`DYdDZhD[lD\pD]tD^xD_|D`€Da„DbˆDcŒDdDe”Df˜DgœDh Di¤Dj¨Dk¬Dl°Dm´Do¸Dp¼DqÀDtÄDuÈDvÌDwÐDxÔDyØDzÜD{àD|äD}èD~ìDðD€ôDøDƒüD„EŠE‹EŒEŽEEE‘E“ E–$E—(E˜,E™0Eš4E›8Eœ<E@EŸDE¢HE¤LE¥PE¨TE©XEª\E«`E¬dE­hE®lE¯pE°tE±xE²|E³€E´„EµˆE·ŒE¸E¹”E»˜E¼œE½ E¾¤EÀ¨EÁpandas/_libs/tslibs/timestamps.pyxname '%U' is not definedgenerator ignored GeneratorExitMissing type objectpandas._libs.tslibs.timestamps._Timestamp.__richcmp__
        Return True if date is last day of the year.

        Returns
        -------
        bool

        See Also
        --------
        Timestamp.is_year_start : Similar property indicating the start of the year.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_year_end
        False

        >>> ts = pd.Timestamp(2020, 12, 31)
        >>> ts.is_year_end
        True
        secondpandas._libs.tslibs.timestamps.__pyx_defaults1pandas._libs.tslibs.timestamps.Timestamp.todayutcoffsetunithour_cresopandas._libs.tslibs.timestamps._Timestamp.day_of_week.__get__dtypedstpandas._libs.tslibs.timestamps.Timestamp.replace__name__ must be set to a string object%sCannot convert %.200s to %.200s__int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.00010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899ndarray_cython_3_3_0a2_dev0.cython_function_or_methodpandas._libs.tslibs.timestamps.Timestamp.tzinfoutctimetuplepandas._libs.tslibs.timestamps.Timestamp.toordinaldoes not matchLZSS string data decompression failedShared Cython type %.200s has the wrong size, try recompilingobject being iterated by 'yield from', or Noneto_pydatetime__setstate__strings are too large to concat
        Return the microsecond of the Timestamp.

        Returns
        -------
        int
            The microsecond of the Timestamp.

        See Also
        --------
        Timestamp.second : Return the second of the Timestamp.
        Timestamp.minute : Return the minute of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30.2304")
        >>> ts.microsecond
        230400
        
        Return numpy datetime64 format with same precision.

        See Also
        --------
        numpy.datetime64 : Numpy datatype for dates and times with high precision.
        Timestamp.to_numpy : Convert the Timestamp to a NumPy datetime64.
        to_datetime : Convert argument to datetime.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14, 15)
        >>> ts.asm8
        numpy.datetime64('2020-03-14T15:00:00.000000')
        pandas._libs.tslibs.timestamps._Timestamp.nanosecond.__get__pandas._libs.tslibs.timestamps._Timestamp._creso.__get__timeflexible_NaTnumpy.core._multiarray_umathpandas._libs.tslibs.timestamps.Timestamp.combinegenexprceilclose() -> raise GeneratorExit inside generator.throw takes between 1 and 3 positional argumentsto_numpypandas._libs.tslibs.timestamps._Timestamp.__setstate__complexfloating__set__metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its basessuper(): empty __class__ cellreplacegi_yieldfrom__qualname__pandas._libs.tslibs.timestamps._Timestamp.to_datetime64pandas._libs.tslibs.timestamps._Timestampisoformatto_periodis_quarter_endasm8integerdatetime.datetime_CAPIpandas._libs.tslibs.timestamps.Timestamp.fromtimestamploader__package__floatingvariablemodule was compiled against NumPy C-API version 0x%x (NumPy 1.20) but the running NumPy has C-API version 0x%x. Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem.pandas._libs.tslibs.timestamps.Timestamp.ctimetoordinalroundpandas._libs.tslibs.timestamps.Timestamp.to_julian_datean integer is required'NoneType' object is not subscriptablepandas._libs.tslibs.timestamps._Timestamp.__reduce__
        The abbreviation associated with self._creso.

        This property returns a string representing the time unit of the Timestamp's
        resolution. It corresponds to the smallest time unit that can be represented
        by this Timestamp object. The possible values are:
        - 's' (second)
        - 'ms' (millisecond)
        - 'us' (microsecond)
        - 'ns' (nanosecond)

        Returns
        -------
        str
            A string abbreviation of the Timestamp's resolution unit:
            - 's' for second
            - 'ms' for millisecond
            - 'us' for microsecond
            - 'ns' for nanosecond

        See Also
        --------
        Timestamp.resolution : Return resolution of the Timestamp.
        Timedelta : A duration expressing the difference between two dates or times.

        Examples
        --------
        >>> pd.Timestamp("2020-01-01 12:34:56").unit
        's'

        >>> pd.Timestamp("2020-01-01 12:34:56.123").unit
        'ms'

        >>> pd.Timestamp("2020-01-01 12:34:56.123456").unit
        'us'

        >>> pd.Timestamp("2020-01-01 12:34:56.123456789").unit
        'ns'
        is_leap_year
        Return the hour of the Timestamp.

        Returns
        -------
        int
            The hour of the Timestamp.

        See Also
        --------
        Timestamp.minute : Return the minute of the Timestamp.
        Timestamp.second : Return the second of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.hour
        16
        pandas._libs.tslibs.timestamps._Timestamp.is_quarter_end.__get__pandas._libs.tslibs.timestamps._Timestamp.second.__get__numpy._core._multiarray_umath_ARRAY_API is NULL pointer_roundpandas._libs.tslibs.timestamps.Timestamp.roundpandas._libs.tslibs.timestamps.Timestamp.replace.validateABCTimestamp_cython_3_3_0a2_dev0_cython_3_3_0a2_dev0.generatorpandas._libs.tslibs.timestamps._Timestamp._from_dt64pandas._libs.tslibs.timestamps._Timestamp.as_unit_date_reprpandas._libs.tslibs.timestamps._Timestamp.year.__get__pandas._libs.tslibs.timedeltasutcfromtimestamppandas._libs.tslibs.timestamps.Timestamp.timetuplepandas._libs.tslibs.timestamps.Timestamp.floorpandas._libs.tslibs.timestamps.Timestamp.ceil_cython_3_3_0a2_dev0._common_types_metatypegi_codepandas._libs.tslibs.timestamps.create_timestamp_from_tssPython objectnormalizefold
        Return the fold value of the Timestamp.

        Returns
        -------
        int
            The fold value of the Timestamp, where 0 indicates the first occurrence
            of the ambiguous time, and 1 indicates the second.

        See Also
        --------
        Timestamp.dst : Return the daylight saving time (DST) adjustment.
        Timestamp.tzinfo : Return the timezone information associated.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-11-03 01:30:00")
        >>> ts.fold
        0
        
        Return the month of the Timestamp.

        Returns
        -------
        int
            The month of the Timestamp.

        See Also
        --------
        Timestamp.day : Return the day of the Timestamp.
        Timestamp.year : Return the year of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.month
        8
        pandas._libs.tslibs.timestamps._Timestamp.day_of_year.__get__inheritance from PyVarObject types like '%.200s' not currently supported_ARRAY_APIFATAL: module compiled as unknown endianpandas._libs.tslibs.timestamps.Timestamp.timetzpandas._libs.tslibs.timestamps.Timestamp.strptimetz_localize'NoneType' object has no attribute '%.30s'getpandas._libs.tslibs.timestamps._Timestamp._can_compareinteger division or modulo by zero_repr_basepandas._libs.tslibs.timestamps._Timestamp.hour.__get__cannot create %.200s instancesdate_Timedelta__mro_entries__ must return a tuplepandas._libs.tslibs.timestamps.Timestamp.utcnowpandas._libs.tslibs.timestamps.Timestamp.time__file__parentsubmodule_search_locationssendclosepandas._libs._cyutilityfunction__pyx_fatalerrorpandas._libs.tslibs.timestamps._Timestamp.to_pydatetime__rsub__pandas._libs.tslibs.timestamps._Timestamp.quarter.__get__pandas._libs.tslibs.timestamps._Timestamp.week.__get__pandas._libs.tslibs.nattypepandas._libs.tslibs.timezonespandas._libs.tslibs.timestamps.MinMaxReso.__get__strftimeExpected %s, got %.200s
        Check if the date is the first day of the month.

        Returns
        -------
        bool
            True if the date is the first day of the month.

        See Also
        --------
        Timestamp.is_month_end : Similar property indicating the last day of the month.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_month_start
        False

        >>> ts = pd.Timestamp(2020, 1, 1)
        >>> ts.is_month_start
        True
        
        Return the week number of the year.

        Returns
        -------
        int

        See Also
        --------
        Timestamp.weekday : Return the day of the week.
        Timestamp.quarter : Return the quarter of the year.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.week
        11
        pandas._libs.tslibs.dtypesNULL result without error in PyObject_Callinteger_op_not_supportednowpandas._libs.tslibs.timestamps.Timestamp.datevalidate__loader__C %.8s %.200s.%.200s has wrong signature (expected %.500s, got %.500s)pandas._libs.tslibs.timestamps._Timestamp._maybe_convert_value_to_localtzquartermicrosecondpandas._libs.tslibs.timestamps.Timestamp.utcfromtimestamptimetzpandas._libs.tslibs.timestamps.Timestamp.__new__.genexprweekdaythrow(typ[,val[,tb]]) -> raise exception in generator,
return next yielded value or raise StopIteration.__name__pandas._libs.tslibs.timestamps._Timestamp._as_cresopandas._libs.tslibs.timestamps._Timestamp.__radd__as_unitis_month_endpandas._libs.tslibs.timestamps._Timestamp._value.__get__flatiterpandas._libs.tslibs.timestamps.Timestamp.utcoffsetpandas/_libs/tslibs/timestamps.pxdqualified name of the generatorpandas._libs.tslibs.timestamps._Timestamp._get_date_name_fieldpandas._libs.tslibs.timestamps._Timestamp.__repr__pandas._libs.tslibs.timestamps._Timestamp.timestamppandas._libs.tslibs.timestamps._Timestamp.month.__get__memoryviewfromtimestamptz_convertFrame of the generatorintto_datetime64value too largeday_namepandas._libs.tslibs.timestamps._Timestamp._from_value_and_resopandas._libs.tslibs.timestamps._Timestamp.__reduce_ex___yearpandas._libs.tslibs.timestamps._Timestamp.is_year_end.__get__numberto_julian_datecython_runtime../venv3.14-android_24_armeabi_v7a/build/lib/python3.14/site-packages/numpy/__init__.cython-30.pxdname of the generator%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectpandas._libs.tslibs.timestamps._Timestamp.__hash___from_value_and_reso
        Return the day of the Timestamp.

        Returns
        -------
        int
            The day of the Timestamp.

        See Also
        --------
        Timestamp.week : Return the week number of the year.
        Timestamp.weekday : Return the day of the week.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.day
        31
        
        Return the minute of the Timestamp.

        Returns
        -------
        int
            The minute of the Timestamp.

        See Also
        --------
        Timestamp.hour : Return the hour of the Timestamp.
        Timestamp.second : Return the second of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.minute
        16
        pandas._libs.tslibs.timestamps._Timestamp.is_month_start.__get__pandas._libs.tslibs.timestamps._Timestamp.days_in_month.__get__pandas._libs.tslibs.timestamps._Timestamp._time_repr.__get__pandas._libs.tslibs.timestamps._Timestamp._nanosecond.__get__BaseOffsetpandas._libs.tslibs.conversion__init____path__init pandas._libs.tslibs.timestampspandas._libs.tslibs.timestamps._Timestamp._get_start_end_field__radd___valuepandas._libs.tslibs.timestamps._Timestamp.unit.__get__pandas._libs.tslibs.timestamps._Timestamp.fold.__get__invalid vtable found for imported typepandas._libs.tslibs.timestamps.__pyx_defaultsdatetimetzinfocharacterufuncmodule compiled against ABI version 0x%x but this version of numpy is 0x%xcombinepandas._libs.tslibs.timestampsShared Cython type %.200s is not a type objectgenerator already executingsend(arg) -> send 'arg' into generator,
return next yielded value or raise StopIteration.__sub__pandas._libs.tslibs.timestamps._Timestamp.month_namepandas._libs.tslibs.timestamps._Timestamp.isoformatvalue
        Return the quarter of the year for the `Timestamp`.

        This property returns an integer representing the quarter of the year in
        which the `Timestamp` falls. The quarters are defined as follows:
        - Q1: January 1 to March 31
        - Q2: April 1 to June 30
        - Q3: July 1 to September 30
        - Q4: October 1 to December 31

        Returns
        -------
        int
            The quarter of the year (1 through 4).

        See Also
        --------
        Timestamp.month : Returns the month of the `Timestamp`.
        Timestamp.year : Returns the year of the `Timestamp`.

        Examples
        --------
        Get the quarter for a `Timestamp`:

        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.quarter
        1

        For a `Timestamp` in the fourth quarter:

        >>> ts = pd.Timestamp(2020, 10, 14)
        >>> ts.quarter
        4
        pandas._libs.tslibs.timestamps._Timestamp._repr_base.__get__timedeltapandas._libs.tslibs.ccalendarpandas._libs.tslibs.timestamps.Timestamp.fromordinalpandas._libs.tslibs.timestamps.Timestamp.utctimetupleorigincompile time Python version %d.%d of module '%.100s' %s runtime version %d.%d_from_dt64
        Check if date is last day of the quarter.

        Returns
        -------
        bool
            True if date is last day of the quarter.

        See Also
        --------
        Timestamp.is_quarter_start : Similar property indicating the quarter start.
        Timestamp.quarter : Return the quarter of the date.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_quarter_end
        False

        >>> ts = pd.Timestamp(2020, 3, 31)
        >>> ts.is_quarter_end
        True
        
        Return day of the week.

        Returns
        -------
        int

        See Also
        --------
        Timestamp.isoweekday : Return the ISO day of the week represented by the date.
        Timestamp.weekday : Return the day of the week represented by the date.
        Timestamp.day_of_year : Return day of the year.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.day_of_week
        5
        pandas._libs.tslibs.timestamps.MinMaxReso.__set__strptimeModule 'timestamps' has already been imported. Re-initialisation is not supported.cannot pickle '%.200s' objectgi_running__int__ returned non-int (type %.200s)pandas._libs.tslibs.timestamps._Timestamp.__sub__pandas._libs.tslibs.timestamps.normalize_i8_stamp_TSObjectLocalizerpandas._libs.tslibs.timestamps.Timestamp.tz_converttimestampspandas._libs.tslibs.timestamps._Timestamp._compare_outside_nanorangemonth_namepandas._libs.tslibs.timestamps._Timestamp.day_namepandas._libs.tslibs.timestamps._Timestamp.value.__get__pandas._libs.tslibs.timestamps._Timestamp.is_year_start.__get__numpy_ARRAY_API is not PyCapsule objecttzname__new__.0%.200s.%.200s is not a type objectpandas._libs.tslibs.timestamps._Timestamp.__rsub__
        Check if the date is the first day of the quarter.

        Returns
        -------
        bool
            True if date is first day of the quarter.

        See Also
        --------
        Timestamp.is_quarter_end : Similar property indicating the quarter end.
        Timestamp.quarter : Return the quarter of the date.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_quarter_start
        False

        >>> ts = pd.Timestamp(2020, 4, 1)
        >>> ts.is_quarter_start
        True
        is_year_endpandas._libs.tslibs.timestamps._Timestamp._date_repr.__get__PeriodDtypeBase__get__pandas._libs.tslibs.timestamps.Timestamp.tzname__orig_bases____reduce____qualname__ must be set to a string object%.200s does not export expected C %.8s %.200spandas._libs.tslibs.timestamps._Timestamp._year.__get__unsignedintegerarraypandas._libs.tslibs.np_datetimenumpy.import_arrayfromordinalbuiltinsItem size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)uint8_tis_year_startyear
        Return the year of the Timestamp.

        Returns
        -------
        int
            The year of the Timestamp.

        See Also
        --------
        Timestamp.month : Return the month of the Timestamp.
        Timestamp.day : Return the day of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.year
        2024
        nanosecondtypepandas._libs.tslibs.timestamps.integer_op_not_supportedpandas._libs.tslibs.timestamps.Timestamp.__new__throwdictpandas._libs.tslibs.timestamps._Timestamp.normalize'%.200s' object is unsliceableis_month_startday_of_year
        Return the day of the year.

        Returns
        -------
        int

        See Also
        --------
        Timestamp.day_of_week : Return day of the week.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.day_of_year
        74
        
        Return the second of the Timestamp.

        Returns
        -------
        int
            The second of the Timestamp.

        See Also
        --------
        Timestamp.microsecond : Return the microsecond of the Timestamp.
        Timestamp.minute : Return the minute of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.second
        30
        
        Return the number of days in the month.

        Returns
        -------
        int

        See Also
        --------
        Timestamp.month_name : Return the month name of the Timestamp with
            specified locale.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.days_in_month
        31
        pandas._libs.tslibs.timestamps.__pyx_scope_struct__genexprbroadcastFATAL: module compiled as little endian, but detected different endianness at runtimepandas._libs.tslibs.timestamps.MinMaxReso.__init__pandas._libs.tslibs.timestamps.Timestamp.dstpandas._libs.tslibs.timestamps.Timestamp._roundpandas._libs.tslibs.timestamps.Timestamp.isoweekdaypandas._libs.tslibs.baseAcquisition count is %d (line %d)strpandas._libs.tslibs.timestamps._Timestamp.to_period
        Return the value of the Timestamp.

        Returns
        -------
        int
            The integer representation of the Timestamp object in nanoseconds
            since the Unix epoch (1970-01-01 00:00:00 UTC).

        See Also
        --------
        Timestamp.second : Return the second of the Timestamp.
        Timestamp.minute : Return the minute of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30")
        >>> ts.value
        1725120990000000000
        day_of_week
        Return the nanosecond of the Timestamp.

        Returns
        -------
        int
            The nanosecond of the Timestamp.

        See Also
        --------
        Timestamp.second : Return the second of the Timestamp.
        Timestamp.microsecond : Return the microsecond of the Timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp("2024-08-31 16:16:30.230400015")
        >>> ts.nanosecond
        15
        %smultiple bases have vtable conflict: '%.200s' and '%.200s'pandas._libs.tslibs.offsetspandas._libs.tslibs.timestamps._unpickle_timestampgenerator raised StopIterationInterpreter change detected - this module can only be loaded into one interpreter per process.__builtins____module____reduce_ex__pandas._libs.tslibs.timestamps._Timestamp.__add__timestampsepweekdays_in_monthpandas._libs.tslibs.timestamps._Timestamp.day.__get__pandas._libs.tslibs.timestamps._Timestamp.minute.__get__ while calling a Python object_unpickle_timestamppandas._libs.tslibs.timestamps.__defaults__isocalendarfloorisoweekdaypandas._libs.tslibs.timestamps._Timestamp._compare_mismatched_resosis_quarter_start
        Return True if date is first day of the year.

        Returns
        -------
        bool

        See Also
        --------
        Timestamp.is_year_end : Similar property indicating the end of the year.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_year_start
        False

        >>> ts = pd.Timestamp(2020, 1, 1)
        >>> ts.is_year_start
        True
        pandas._libs.tslibs.timestamps._Timestamp.is_month_end.__get__pandas._libs.tslibs.timestamps._Timestamp.microsecond.__get__pandas._libs.tslibs.tzconversionpandas._libs.tslibs.timestamps.Timestamp.nowtodaypandas._libs.tslibs.timestamps.Timestamp.strftimetimetuple__debug__gi_frameunsupported operand type(s) for %.3s: '%.200s' and '%.200s'__add__timespec
        Check if the date is the last day of the month.

        Returns
        -------
        bool
            True if the date is the last day of the month.

        See Also
        --------
        Timestamp.is_month_start : Similar property indicating month start.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_month_end
        False

        >>> ts = pd.Timestamp(2020, 12, 31)
        >>> ts.is_month_end
        True
        day_time_repr_nanosecondpandas._libs.tslibs.timestamps._Timestamp.is_quarter_start.__get__pandas._libs.tslibs.timestamps._Timestamp.asm8.__get__signedintegerinexactpandas._pandas_datetime_CAPIutcnowctimepandas._libs.tslibs.timestamps.Timestamp.tz_localizepandas._libs.tslibs.timestamps.Timestamp.weekday__pyx_capi__Buffer has wrong number of dimensions (expected %d, got %d)pandas._libs.tslibs.timestamps._Timestamp.to_numpy
        Return True if year is a leap year.

        A leap year is a year, which has 366 days (instead of 365) including 29th of
        February as an intercalary day. Leap years are years which are multiples of
        four with the exception of years divisible by 100 but not by 400.

        Returns
        -------
        bool
            True if year is a leap year, else False

        See Also
        --------
        Period.is_leap_year : Return True if the period’s year is in a leap year.
        DatetimeIndex.is_leap_year : Boolean indicator if the date belongs to a
            leap year.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14)
        >>> ts.is_leap_year
        True
        monthminutegenericpandas._libs.tslibs.timestamps.Timestamp.isocalendarpandas._libs.tslibs.timestamps.Timestamp.tznamelocal variable '%s' referenced before assignment
_Timestamp is a c-defined subclass of datetime.datetime

_Timestamp is PITA. Because we inherit from datetime, which has very specific
construction requirements, we need to do object instantiation in python
(see Timestamp class below). This will serve as a C extension type that
shadows the python class, where we do any heavy lifting.
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        Return the day name of the Timestamp with specified locale.

        Parameters
        ----------
        locale : str, default None (English locale)
            Locale determining the language in which to return the day name.

        Returns
        -------
        str

        See Also
        --------
        Timestamp.day_of_week : Return day of the week.
        Timestamp.day_of_year : Return day of the year.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts.day_name()
        'Saturday'

        Analogous for ``pd.NaT``:

        >>> pd.NaT.day_name()
        nan
        
        Return the month name of the Timestamp with specified locale.

        This method returns the full name of the month corresponding to the
        `Timestamp`, such as 'January', 'February', etc. The month name can
        be returned in a specified locale if provided; otherwise, it defaults
        to the English locale.

        Parameters
        ----------
        locale : str, default None (English locale)
            Locale determining the language in which to return the month name.

        Returns
        -------
        str
            The full month name as a string.

        See Also
        --------
        Timestamp.day_name : Returns the name of the day of the week.
        Timestamp.strftime : Returns a formatted string of the Timestamp.
        datetime.datetime.strftime : Returns a string representing the date and time.

        Examples
        --------
        Get the month name in English (default):

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts.month_name()
        'March'

        Analogous for ``pd.NaT``:

        >>> pd.NaT.month_name()
        nan
        
        Normalize Timestamp to midnight, preserving tz information.

        This method sets the time component of the `Timestamp` to midnight (00:00:00),
        while preserving the date and time zone information. It is useful when you
        need to standardize the time across different `Timestamp` objects without
        altering the time zone or the date.

        Returns
        -------
        Timestamp

        See Also
        --------
        Timestamp.floor : Rounds `Timestamp` down to the nearest frequency.
        Timestamp.ceil : Rounds `Timestamp` up to the nearest frequency.
        Timestamp.round : Rounds `Timestamp` to the nearest frequency.

        Examples
        --------
        >>> ts = pd.Timestamp(2020, 3, 14, 15, 30)
        >>> ts.normalize()
        Timestamp('2020-03-14 00:00:00')
        
        Return the time formatted according to ISO 8601.

        The full format looks like 'YYYY-MM-DD HH:MM:SS.mmmmmmnnn'.
        By default, the fractional part is omitted if self.microsecond == 0
        and self._nanosecond == 0.

        If self.tzinfo is not None, the UTC offset is also attached,
        giving a full format of 'YYYY-MM-DD HH:MM:SS.mmmmmmnnn+HH:MM'.

        Parameters
        ----------
        sep : str, default 'T'
            String used as the separator between the date and time.

        timespec : str, default 'auto'
            Specifies the number of additional terms of the time to include.
            The valid values are 'auto', 'hours', 'minutes', 'seconds',
            'milliseconds', 'microseconds', and 'nanoseconds'.

        Returns
        -------
        str

        See Also
        --------
        Timestamp.strftime : Return a formatted string.
        Timestamp.isocalendar : Return a tuple containing ISO year, week number and
            weekday.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts.isoformat()
        '2020-03-14T15:32:52.192548651'
        >>> ts.isoformat(timespec='microseconds')
        '2020-03-14T15:32:52.192548'
        
        Convert the underlying int64 representation to the given unit.

        Parameters
        ----------
        unit : {"ns", "us", "ms", "s"}
        round_ok : bool, default True
            If False and the conversion requires rounding, raise.

        Returns
        -------
        Timestamp

        See Also
        --------
        Timestamp.asm8 : Return numpy datetime64 format with same precision.
        Timestamp.to_pydatetime : Convert Timestamp object to a native
            Python datetime object.
        to_timedelta : Convert argument into timedelta object,
            which can represent differences in times.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 00:00:00.01')
        >>> ts
        Timestamp('2023-01-01 00:00:00.010000')
        >>> ts.unit
        'ms'
        >>> ts = ts.as_unit('s')
        >>> ts
        Timestamp('2023-01-01 00:00:00')
        >>> ts.unit
        's'
        
        Return POSIX timestamp as float.

        This method converts the `Timestamp` object to a POSIX timestamp, which is
        the number of seconds since the Unix epoch (January 1, 1970). The returned
        value is a floating-point number, where the integer part represents the
        seconds, and the fractional part represents the microseconds.

        Returns
        -------
        float
            The POSIX timestamp representation of the `Timestamp` object.

        See Also
        --------
        Timestamp.fromtimestamp : Construct a `Timestamp` from a POSIX timestamp.
        datetime.datetime.timestamp : Equivalent method from the `datetime` module.
        Timestamp.to_pydatetime : Convert the `Timestamp` to a `datetime` object.
        Timestamp.to_datetime64 : Converts `Timestamp` to `numpy.datetime64`.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548')
        >>> ts.timestamp()
        1584199972.192548
        
        Convert the Timestamp to a NumPy datetime64.

        This is an alias method for `Timestamp.to_datetime64()`. The dtype and
        copy parameters are available here only for compatibility. Their values
        will not affect the return value.

        Parameters
        ----------
        dtype : dtype, optional
            Data type of the output, ignored in this method as the return type
            is always `numpy.datetime64`.
        copy : bool, default False
            Whether to ensure that the returned value is a new object. This
            parameter is also ignored as the method does not support copying.

        Returns
        -------
        numpy.datetime64

        See Also
        --------
        DatetimeIndex.to_numpy : Similar method for DatetimeIndex.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts.to_numpy()
        numpy.datetime64('2020-03-14T15:32:52.192548651')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.to_numpy()
        numpy.datetime64('NaT', 'ns')
        
        Return a period of which this timestamp is an observation.

        This method converts the given Timestamp to a Period object,
        which represents a span of time,such as a year, month, etc.,
        based on the specified frequency.

        Parameters
        ----------
        freq : str, optional
            Frequency string for the period (e.g., 'Y', 'M', 'W'). Defaults to `None`.

        See Also
        --------
        Timestamp : Represents a specific timestamp.
        Period : Represents a span of time.
        to_period : Converts an object to a Period.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> # Year end frequency
        >>> ts.to_period(freq='Y')
        Period('2020', 'Y-DEC')

        >>> # Month end frequency
        >>> ts.to_period(freq='M')
        Period('2020-03', 'M')

        >>> # Weekly frequency
        >>> ts.to_period(freq='W')
        Period('2020-03-09/2020-03-15', 'W-SUN')

        >>> # Quarter end frequency
        >>> ts.to_period(freq='Q')
        Period('2020Q1', 'Q-DEC')
        
        Convert a Timestamp object to a native Python datetime object.

        This method is useful for when you need to utilize a pandas Timestamp
        object in contexts where native Python datetime objects are expected
        or required. The conversion discards the nanoseconds component, and a
        warning can be issued in such cases if desired.

        Parameters
        ----------
        warn : bool, default True
            If True, issues a warning when the timestamp includes nonzero
            nanoseconds, as these will be discarded during the conversion.

        Returns
        -------
        datetime.datetime or NaT
            Returns a datetime.datetime object representing the timestamp,
            with year, month, day, hour, minute, second, and microsecond components.
            If the timestamp is NaT (Not a Time), returns NaT.

        See Also
        --------
        datetime.datetime : The standard Python datetime class that this method
            returns.
        Timestamp.timestamp : Convert a Timestamp object to POSIX timestamp.
        Timestamp.to_datetime64 : Convert a Timestamp object to numpy.datetime64.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548')
        >>> ts.to_pydatetime()
        datetime.datetime(2020, 3, 14, 15, 32, 52, 192548)

        Analogous for ``pd.NaT``:

        >>> pd.NaT.to_pydatetime()
        NaT
        
        Return a NumPy datetime64 object with same precision.

        This method returns a numpy.datetime64 object with the same
        date and time information and precision as the pd.Timestamp object.

        See Also
        --------
        numpy.datetime64 : Class to represent dates and times with high precision.
        Timestamp.to_numpy : Alias for this method.
        Timestamp.asm8 : Alias for this method.
        pd.to_datetime : Convert argument to datetime.

        Examples
        --------
        >>> ts = pd.Timestamp(year=2023, month=1, day=1,
        ...                   hour=10, second=15)
        >>> ts
        Timestamp('2023-01-01 10:00:15')
        >>> ts.to_datetime64()
        numpy.datetime64('2023-01-01T10:00:15.000000')
        
        Construct a timestamp from a proleptic Gregorian ordinal.

        This method creates a `Timestamp` object corresponding to the given
        proleptic Gregorian ordinal, which is a count of days from January 1,
        0001 (using the proleptic Gregorian calendar). The time part of the
        `Timestamp` is set to midnight (00:00:00) by default.

        Parameters
        ----------
        ordinal : int
            Date corresponding to a proleptic Gregorian ordinal.
        tz : str, zoneinfo.ZoneInfo, pytz.timezone, dateutil.tz.tzfile or None
            Time zone for the Timestamp.

        Returns
        -------
        Timestamp
            A `Timestamp` object representing the specified ordinal date.

        See Also
        --------
        Timestamp : Represents a single timestamp, similar to `datetime`.
        to_datetime : Converts various types of data to datetime.

        Notes
        -----
        By definition there cannot be any tz info on the ordinal itself.

        Examples
        --------
        Convert an ordinal to a `Timestamp`:

        >>> pd.Timestamp.fromordinal(737425)
        Timestamp('2020-01-01 00:00:00')

        Create a `Timestamp` from an ordinal with timezone information:

        >>> pd.Timestamp.fromordinal(737425, tz='UTC')
        Timestamp('2020-01-01 00:00:00+0000', tz='UTC')
        
        Return new Timestamp object representing current time local to tz.

        This method returns a new `Timestamp` object that represents the current time.
        If a timezone is provided, either through a timezone object or an IANA
        standard timezone identifier, the current time will be localized to that
        timezone.
        Otherwise, it returns the current local time.

        Parameters
        ----------
        tz : str or timezone object, default None
            Timezone to localize to.

        See Also
        --------
        to_datetime : Convert argument to datetime.
        Timestamp.utcnow : Return a new Timestamp representing UTC day and time.
        Timestamp.today : Return the current time in the local timezone.

        Examples
        --------
        >>> pd.Timestamp.now()  # doctest: +SKIP
        Timestamp('2020-11-16 22:06:16.378782')

        If you want a specific timezone, in this case 'Brazil/East':

        >>> pd.Timestamp.now('Brazil/East')  # doctest: +SKIP
        Timestamp('2025-11-11 22:17:59.609943-03:00)

        Analogous for ``pd.NaT``:

        >>> pd.NaT.now()
        NaT
        
        Return the current time in the local timezone.

        This differs from datetime.today() in that it can be localized to a
        passed timezone.

        Parameters
        ----------
        tz : str or timezone object, default None
            Timezone to localize to.

        See Also
        --------
        datetime.datetime.today : Returns the current local date.
        Timestamp.now : Returns current time with optional timezone.
        Timestamp : A class representing a specific timestamp.

        Examples
        --------
        >>> pd.Timestamp.today()    # doctest: +SKIP
        Timestamp('2020-11-16 22:37:39.969883')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.today()
        NaT
        
        Timestamp.utcnow()

        Return a new Timestamp representing UTC day and time.

        See Also
        --------
        Timestamp : Constructs an arbitrary datetime.
        Timestamp.now : Return the current local date and time, which
            can be timezone-aware.
        Timestamp.today : Return the current local date and time with
            timezone information set to None.
        to_datetime : Convert argument to datetime.
        date_range : Return a fixed frequency DatetimeIndex.
        Timestamp.utctimetuple : Return UTC time tuple, compatible with
            time.localtime().

        Examples
        --------
        >>> pd.Timestamp.utcnow()   # doctest: +SKIP
        Timestamp('2020-11-16 22:50:18.092888+0000', tz='UTC')
        
        Timestamp.utcfromtimestamp(ts)

        Construct a timezone-aware UTC datetime from a POSIX timestamp.

        This method creates a datetime object from a POSIX timestamp, keeping the
        Timestamp object's timezone.

        Parameters
        ----------
        ts : float
            POSIX timestamp.

        See Also
        --------
        Timezone.tzname : Return time zone name.
        Timestamp.utcnow : Return a new Timestamp representing UTC day and time.
        Timestamp.fromtimestamp : Transform timestamp[, tz] to tz's local
            time from POSIX timestamp.

        Notes
        -----
        Timestamp.utcfromtimestamp behavior differs from datetime.utcfromtimestamp
        in returning a timezone-aware object.

        Examples
        --------
        >>> pd.Timestamp.utcfromtimestamp(1584199972)
        Timestamp('2020-03-14 15:32:52+0000', tz='UTC')
        
        Create a `Timestamp` object from a POSIX timestamp.

        This method converts a POSIX timestamp (the number of seconds since
        January 1, 1970, 00:00:00 UTC) into a `Timestamp` object. The resulting
        `Timestamp` can be localized to a specific time zone if provided.

        Parameters
        ----------
        ts : float
            The POSIX timestamp to convert, representing seconds since
            the epoch (1970-01-01 00:00:00 UTC).
        tz : str, zoneinfo.ZoneInfo, pytz.timezone, dateutil.tz.tzfile, optional
            Time zone for the `Timestamp`. If not provided, the `Timestamp` will
            be timezone-naive (i.e., without time zone information).

        Returns
        -------
        Timestamp
            A `Timestamp` object representing the given POSIX timestamp.

        See Also
        --------
        Timestamp : Represents a single timestamp, similar to `datetime`.
        to_datetime : Converts various types of data to datetime.
        datetime.datetime.fromtimestamp : Returns a datetime from a POSIX timestamp.

        Examples
        --------
        Convert a POSIX timestamp to a `Timestamp`:

        >>> pd.Timestamp.fromtimestamp(1584199972)  # doctest: +SKIP
        Timestamp('2020-03-14 15:32:52')

        Note that the output may change depending on your local time and time zone:

        >>> pd.Timestamp.fromtimestamp(1584199972, tz='UTC')  # doctest: +SKIP
        Timestamp('2020-03-14 15:32:52+0000', tz='UTC')
        
        Return a formatted string of the Timestamp.

        Parameters
        ----------
        format : str
            Format string to convert Timestamp to string.
            See strftime documentation for more information on the format string:
            https://docs.python.org/3/library/datetime.html#strftime-and-strptime-behavior.

        See Also
        --------
        Timestamp.isoformat : Return the time formatted according to ISO 8601.
        pd.to_datetime : Convert argument to datetime.
        Period.strftime : Format a single Period.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts.strftime('%Y-%m-%d %X')
        '2020-03-14 15:32:52'
        
        Return a ctime() style string representing the Timestamp.

        This method returns a string representing the date and time
        in the format returned by the standard library's `time.ctime()`
        function, which is typically in the form 'Day Mon DD HH:MM:SS YYYY'.

        If the `Timestamp` is outside the range supported by Python's
        standard library, a `NotImplementedError` is raised.

        Returns
        -------
        str
            A string representing the Timestamp in ctime format.

        See Also
        --------
        time.ctime : Return a string representing time in ctime format.
        Timestamp : Represents a single timestamp, similar to `datetime`.
        datetime.datetime.ctime : Return a ctime style string from a datetime object.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00.00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.ctime()
        'Sun Jan  1 10:00:00 2023'
        
        Returns `datetime.date` with the same year, month, and day.

        This method extracts the date component from the `Timestamp` and returns
        it as a `datetime.date` object, discarding the time information.

        Returns
        -------
        datetime.date
            The date part of the `Timestamp`.

        See Also
        --------
        Timestamp : Represents a single timestamp, similar to `datetime`.
        datetime.datetime.date : Extract the date component from a `datetime` object.

        Examples
        --------
        Extract the date from a Timestamp:

        >>> ts = pd.Timestamp('2023-01-01 10:00:00.00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.date()
        datetime.date(2023, 1, 1)
        
        Return the daylight saving time (DST) adjustment.

        This method returns the DST adjustment as a `datetime.timedelta` object
        if the Timestamp is timezone-aware and DST is applicable.

        See Also
        --------
        Timestamp.tz_localize : Localize the Timestamp to a timezone.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.

        Examples
        --------
        >>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')
        >>> ts
        Timestamp('2000-06-01 00:00:00+0200', tz='Europe/Brussels')
        >>> ts.dst()
        datetime.timedelta(seconds=3600)
        
        Return a named tuple containing ISO year, week number, and weekday.

        See Also
        --------
        DatetimeIndex.isocalendar : Return a 3-tuple containing ISO year,
            week number, and weekday for the given DatetimeIndex object.
        datetime.date.isocalendar : The equivalent method for `datetime.date` objects.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.isocalendar()
        datetime.IsoCalendarDate(year=2022, week=52, weekday=7)
        
        Return time zone name.

        This method returns the name of the Timestamp's time zone as a string.

        See Also
        --------
        Timestamp.tzinfo : Returns the timezone information of the Timestamp.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
        >>> ts
        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
        >>> ts.tzname()
        'CET'
        
        Returns the timezone info of the Timestamp.

        This property returns a `datetime.tzinfo` object if the Timestamp
        is timezone-aware. If the Timestamp has no timezone, it returns `None`.
        If the Timestamp is in UTC or a fixed-offset timezone,
        it returns `datetime.timezone`. If the Timestamp uses an
        IANA timezone (e.g., "America/New_York"), it returns `zoneinfo.ZoneInfo`.

        See Also
        --------
        Timestamp.tz : Alias for `tzinfo`, may return a `zoneinfo.ZoneInfo` object.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
        Timestamp.tz_localize : Localize the Timestamp to a specific timezone.

        Examples
        --------
        >>> ts = pd.Timestamp("2023-01-01 12:00:00", tz="UTC")
        >>> ts.tzinfo
        datetime.timezone.utc

        >>> ts_naive = pd.Timestamp("2023-01-01 12:00:00")
        >>> ts_naive.tzinfo
        
        Return utc offset.

        This method returns the difference between UTC and the local time
        as a `timedelta` object. It is useful for understanding the time
        difference between the current timezone and UTC.

        Returns
        -------
        timedelta
            The difference between UTC and the local time as a `timedelta` object.

        See Also
        --------
        datetime.datetime.utcoffset :
            Standard library method to get the UTC offset of a datetime object.
        Timestamp.tzname : Return the name of the timezone.
        Timestamp.dst : Return the daylight saving time (DST) adjustment.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
        >>> ts
        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
        >>> ts.utcoffset()
        datetime.timedelta(seconds=3600)
        
        Return UTC time tuple, compatible with `time.localtime()`.

        This method converts the Timestamp to UTC and returns a time tuple
        containing 9 components: year, month, day, hour, minute, second,
        weekday, day of year, and DST flag. This is particularly useful for
        converting a Timestamp to a format compatible with time module functions.

        Returns
        -------
        time.struct_time
            A time.struct_time object representing the UTC time.

        See Also
        --------
        datetime.datetime.utctimetuple :
            Return UTC time tuple, compatible with time.localtime().
        Timestamp.timetuple : Return time tuple of local time.
        time.struct_time : Time tuple structure used by time functions.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
        >>> ts
        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
        >>> ts.utctimetuple()
        time.struct_time(tm_year=2023, tm_mon=1, tm_mday=1, tm_hour=9,
        tm_min=0, tm_sec=0, tm_wday=6, tm_yday=1, tm_isdst=0)
        
        Return time object with same time but with tzinfo=None.

        This method extracts the time part of the `Timestamp` object, excluding any
        timezone information. It returns a `datetime.time` object which only represents
        the time (hours, minutes, seconds, and microseconds).

        See Also
        --------
        Timestamp.date : Return date object with same year, month and day.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
        Timestamp.tz_localize : Localize the Timestamp to a timezone.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.time()
        datetime.time(10, 0)
        
        Return time tuple, compatible with time.localtime().

        This method converts the `Timestamp` into a time tuple, which is compatible
        with functions like `time.localtime()`. The time tuple is a named tuple with
        attributes such as year, month, day, hour, minute, second, weekday,
        day of the year, and daylight savings indicator.

        See Also
        --------
        time.localtime : Converts a POSIX timestamp into a time tuple.
        Timestamp : The `Timestamp` that represents a specific point in time.
        datetime.datetime.timetuple : Equivalent method in the `datetime` module.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.timetuple()
        time.struct_time(tm_year=2023, tm_mon=1, tm_mday=1,
        tm_hour=10, tm_min=0, tm_sec=0, tm_wday=6, tm_yday=1, tm_isdst=-1)
        
        Return time object with same time and tzinfo.

        This method returns a datetime.time object with
        the time and tzinfo corresponding to the pd.Timestamp
        object, ignoring any information about the day/date.

        See Also
        --------
        datetime.datetime.timetz : Return datetime.time object with the
            same time attributes as the datetime object.
        datetime.time : Class to represent the time of day, independent
            of any particular day.
        datetime.datetime.tzinfo : Attribute of datetime.datetime objects
            representing the timezone of the datetime object.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00', tz='Europe/Brussels')
        >>> ts
        Timestamp('2023-01-01 10:00:00+0100', tz='Europe/Brussels')
        >>> ts.timetz()
        datetime.time(10, 0, tzinfo=<DstTzInfo 'Europe/Brussels' CET+1:00:00 STD>)
        
        Return proleptic Gregorian ordinal. January 1 of year 1 is day 1.

        The proleptic Gregorian ordinal is a continuous count of days since
        January 1 of year 1, which is considered day 1. This method converts
        the `Timestamp` to its equivalent ordinal number, useful for date arithmetic
        and comparison operations.

        See Also
        --------
        datetime.datetime.toordinal : Equivalent method in the `datetime` module.
        Timestamp : The `Timestamp` that represents a specific point in time.
        Timestamp.fromordinal : Create a `Timestamp` from an ordinal.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:50')
        >>> ts
        Timestamp('2023-01-01 10:00:50')
        >>> ts.toordinal()
        738521
        
        Convert string argument to datetime.

        This method is not implemented; calling it will raise NotImplementedError.
        Use pd.to_datetime() instead.

        Parameters
        ----------
        date_string : str
            String to convert to a datetime.
        format : str, default None
            The format string to parse time, e.g. "%d/%m/%Y".

        See Also
        --------
        pd.to_datetime : Convert argument to datetime.
        datetime.datetime.strptime : Return a datetime corresponding to a string
            representing a date and time, parsed according to a separate
            format string.
        datetime.datetime.strftime : Return a string representing the date and
            time, controlled by an explicit format string.
        Timestamp.isoformat : Return the time formatted according to ISO 8601.

        Examples
        --------
        >>> pd.Timestamp.strptime("2023-01-01", "%d/%m/%y")
        Traceback (most recent call last):
        NotImplementedError
        
        Timestamp.combine(date, time)

        Combine a date and time into a single Timestamp object.

        This method takes a `date` object and a `time` object
        and combines them into a single `Timestamp`
        that has the same date and time fields.

        Parameters
        ----------
        date : datetime.date
            The date part of the Timestamp.
        time : datetime.time
            The time part of the Timestamp.

        Returns
        -------
        Timestamp
            A new `Timestamp` object representing the combined date and time.

        See Also
        --------
        Timestamp : Represents a single timestamp, similar to `datetime`.
        to_datetime : Converts various types of data to datetime.

        Examples
        --------
        >>> from datetime import date, time
        >>> pd.Timestamp.combine(date(2020, 3, 14), time(15, 30, 15))
        Timestamp('2020-03-14 15:30:15')
        
        Round the Timestamp to the specified resolution.

        This method rounds the given Timestamp down to a specified frequency
        level. It is particularly useful in data analysis to normalize timestamps
        to regular frequency intervals. For instance, rounding to the nearest
        minute, hour, or day can help in time series comparisons or resampling
        operations.

        Parameters
        ----------
        freq : str
            Frequency string indicating the rounding resolution.
        ambiguous : bool or {'raise', 'NaT'}, default 'raise'
            The behavior is as follows:

            * bool contains flags to determine if time is dst or not (note
              that this flag is only applicable for ambiguous fall dst dates).
            * 'NaT' will return NaT for an ambiguous time.
            * 'raise' will raise a ValueError for an ambiguous time.

        nonexistent : {'raise', 'shift_forward', 'shift_backward', 'NaT', timedelta}, default 'raise'
            A nonexistent time does not exist in a particular timezone
            where clocks moved forward due to DST.

            * 'shift_forward' will shift the nonexistent time forward to the
              closest existing time.
            * 'shift_backward' will shift the nonexistent time backward to the
              closest existing time.
            * 'NaT' will return NaT where there are nonexistent times.
            * timedelta objects will shift nonexistent times by the timedelta.
            * 'raise' will raise a ValueError if there are
              nonexistent times.

        Returns
        -------
        a new Timestamp rounded to the given resolution of `freq`

        Raises
        ------
        ValueError if the freq cannot be converted

        See Also
        --------
        datetime.round : Similar behavior in native Python datetime module.
        Timestamp.floor : Round the Timestamp downward to the nearest multiple
            of the specified frequency.
        Timestamp.ceil : Round the Timestamp upward to the nearest multiple of
            the specified frequency.

        Notes
        -----
        If the Timestamp has a timezone, rounding will take place relative to the
        local ("wall") time and re-localized to the same timezone. When rounding
        near daylight savings time, use ``nonexistent`` and ``ambiguous`` to
        control the re-localization behavior.

        Examples
        --------
        Create a timestamp object:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')

        A timestamp can be rounded using multiple frequency units:

        >>> ts.round(freq='h')  # hour
        Timestamp('2020-03-14 16:00:00')

        >>> ts.round(freq='min')  # minute
        Timestamp('2020-03-14 15:33:00')

        >>> ts.round(freq='s')  # seconds
        Timestamp('2020-03-14 15:32:52')

        >>> ts.round(freq='ms')  # milliseconds
        Timestamp('2020-03-14 15:32:52.193000')

        ``freq`` can also be a multiple of a single unit, like '5min' (i.e.  5 minutes):

        >>> ts.round(freq='5min')
        Timestamp('2020-03-14 15:35:00')

        or a combination of multiple units, like '1h30min' (i.e. 1 hour and 30 minutes):

        >>> ts.round(freq='1h30min')
        Timestamp('2020-03-14 15:00:00')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.round()
        NaT

        When rounding near a daylight savings time transition, use ``ambiguous`` or
        ``nonexistent`` to control how the timestamp should be re-localized.

        >>> ts_tz = pd.Timestamp("2021-10-31 01:30:00").tz_localize("Europe/Amsterdam")

        >>> ts_tz.round("h", ambiguous=False)
        Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')

        >>> ts_tz.round("h", ambiguous=True)
        Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')
        
        Return a new Timestamp floored to this resolution.

        Parameters
        ----------
        freq : str
            Frequency string indicating the flooring resolution.
        ambiguous : bool or {'raise', 'NaT'}, default 'raise'
            The behavior is as follows:

            * bool contains flags to determine if time is dst or not (note
              that this flag is only applicable for ambiguous fall dst dates).
            * 'NaT' will return NaT for an ambiguous time.
            * 'raise' will raise a ValueError for an ambiguous time.

        nonexistent : {'raise', 'shift_forward', 'shift_backward', 'NaT', timedelta}, default 'raise'
            A nonexistent time does not exist in a particular timezone
            where clocks moved forward due to DST.

            * 'shift_forward' will shift the nonexistent time forward to the
              closest existing time.
            * 'shift_backward' will shift the nonexistent time backward to the
              closest existing time.
            * 'NaT' will return NaT where there are nonexistent times.
            * timedelta objects will shift nonexistent times by the timedelta.
            * 'raise' will raise a ValueError if there are
              nonexistent times.

        Raises
        ------
        ValueError if the freq cannot be converted.

        See Also
        --------
        Timestamp.ceil : Round up a Timestamp to the specified resolution.
        Timestamp.round : Round a Timestamp to the specified resolution.
        Series.dt.floor : Round down the datetime values in a Series.

        Notes
        -----
        If the Timestamp has a timezone, flooring will take place relative to the
        local ("wall") time and re-localized to the same timezone. When flooring
        near daylight savings time, use ``nonexistent`` and ``ambiguous`` to
        control the re-localization behavior.

        Examples
        --------
        Create a timestamp object:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')

        A timestamp can be floored using multiple frequency units:

        >>> ts.floor(freq='h')  # hour
        Timestamp('2020-03-14 15:00:00')

        >>> ts.floor(freq='min')  # minute
        Timestamp('2020-03-14 15:32:00')

        >>> ts.floor(freq='s')  # seconds
        Timestamp('2020-03-14 15:32:52')

        >>> ts.floor(freq='ns')  # nanoseconds
        Timestamp('2020-03-14 15:32:52.192548651')

        ``freq`` can also be a multiple of a single unit, like '5min' (i.e.  5 minutes):

        >>> ts.floor(freq='5min')
        Timestamp('2020-03-14 15:30:00')

        or a combination of multiple units, like '1h30min' (i.e. 1 hour and 30 minutes):

        >>> ts.floor(freq='1h30min')
        Timestamp('2020-03-14 15:00:00')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.floor()
        NaT

        When rounding near a daylight savings time transition, use ``ambiguous`` or
        ``nonexistent`` to control how the timestamp should be re-localized.

        >>> ts_tz = pd.Timestamp("2021-10-31 03:30:00").tz_localize("Europe/Amsterdam")

        >>> ts_tz.floor("2h", ambiguous=False)
        Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')

        >>> ts_tz.floor("2h", ambiguous=True)
        Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')
        
        Return a new Timestamp ceiled to this resolution.

        Parameters
        ----------
        freq : str
            Frequency string indicating the ceiling resolution.
        ambiguous : bool or {'raise', 'NaT'}, default 'raise'
            The behavior is as follows:

            * bool contains flags to determine if time is dst or not (note
              that this flag is only applicable for ambiguous fall dst dates).
            * 'NaT' will return NaT for an ambiguous time.
            * 'raise' will raise a ValueError for an ambiguous time.

        nonexistent : {'raise', 'shift_forward', 'shift_backward', 'NaT', timedelta}, default 'raise'
            A nonexistent time does not exist in a particular timezone
            where clocks moved forward due to DST.

            * 'shift_forward' will shift the nonexistent time forward to the
              closest existing time.
            * 'shift_backward' will shift the nonexistent time backward to the
              closest existing time.
            * 'NaT' will return NaT where there are nonexistent times.
            * timedelta objects will shift nonexistent times by the timedelta.
            * 'raise' will raise a ValueError if there are
              nonexistent times.

        Raises
        ------
        ValueError if the freq cannot be converted.

        See Also
        --------
        Timestamp.floor : Round down a Timestamp to the specified resolution.
        Timestamp.round : Round a Timestamp to the specified resolution.
        Series.dt.ceil : Ceil the datetime values in a Series.

        Notes
        -----
        If the Timestamp has a timezone, ceiling will take place relative to the
        local ("wall") time and re-localized to the same timezone. When ceiling
        near daylight savings time, use ``nonexistent`` and ``ambiguous`` to
        control the re-localization behavior.

        Examples
        --------
        Create a timestamp object:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')

        A timestamp can be ceiled using multiple frequency units:

        >>> ts.ceil(freq='h')  # hour
        Timestamp('2020-03-14 16:00:00')

        >>> ts.ceil(freq='min')  # minute
        Timestamp('2020-03-14 15:33:00')

        >>> ts.ceil(freq='s')  # seconds
        Timestamp('2020-03-14 15:32:53')

        >>> ts.ceil(freq='us')  # microseconds
        Timestamp('2020-03-14 15:32:52.192549')

        ``freq`` can also be a multiple of a single unit, like '5min' (i.e.  5 minutes):

        >>> ts.ceil(freq='5min')
        Timestamp('2020-03-14 15:35:00')

        or a combination of multiple units, like '1h30min' (i.e. 1 hour and 30 minutes):

        >>> ts.ceil(freq='1h30min')
        Timestamp('2020-03-14 16:30:00')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.ceil()
        NaT

        When rounding near a daylight savings time transition, use ``ambiguous`` or
        ``nonexistent`` to control how the timestamp should be re-localized.

        >>> ts_tz = pd.Timestamp("2021-10-31 01:30:00").tz_localize("Europe/Amsterdam")

        >>> ts_tz.ceil("h", ambiguous=False)
        Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')

        >>> ts_tz.ceil("h", ambiguous=True)
        Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')
        
        Alias for tzinfo.

        The `tz` property provides a simple and direct way to retrieve the timezone
        information of a `Timestamp` object. It is particularly useful when working
        with time series data that includes timezone information, allowing for easy
        access and manipulation of the timezone context.

        See Also
        --------
        Timestamp.tzinfo : Returns the timezone information of the Timestamp.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
        Timestamp.tz_localize : Localize the Timestamp to a timezone.

        Examples
        --------
        >>> ts = pd.Timestamp(1584226800, unit='s', tz='Europe/Stockholm')
        >>> ts.tz
        zoneinfo.ZoneInfo(key='Europe/Stockholm')
        
        Localize the Timestamp to a timezone.

        Convert naive Timestamp to local time zone or remove
        timezone from timezone-aware Timestamp.

        Parameters
        ----------
        tz : str, zoneinfo.ZoneInfo, pytz.timezone, dateutil.tz.tzfile or None
            Time zone for time which Timestamp will be converted to.
            None will remove timezone holding local time.

        ambiguous : bool, 'NaT', default 'raise'
            When clocks moved backward due to DST, ambiguous times may arise.
            For example in Central European Time (UTC+01), when going from
            03:00 DST to 02:00 non-DST, 02:30:00 local time occurs both at
            00:30:00 UTC and at 01:30:00 UTC. In such a situation, the
            `ambiguous` parameter dictates how ambiguous times should be
            handled.

            The behavior is as follows:

            * bool contains flags to determine if time is dst or not (note
              that this flag is only applicable for ambiguous fall dst dates).
            * 'NaT' will return NaT for an ambiguous time.
            * 'raise' will raise a ValueError for an ambiguous time.

        nonexistent : 'shift_forward', 'shift_backward', 'NaT', timedelta, default 'raise'
            A nonexistent time does not exist in a particular timezone
            where clocks moved forward due to DST.

            The behavior is as follows:

            * 'shift_forward' will shift the nonexistent time forward to the
              closest existing time.
            * 'shift_backward' will shift the nonexistent time backward to the
              closest existing time.
            * 'NaT' will return NaT where there are nonexistent times.
            * timedelta objects will shift nonexistent times by the timedelta.
            * 'raise' will raise a ValueError if there are
              nonexistent times.

        Returns
        -------
        localized : Timestamp

        Raises
        ------
        TypeError
            If the Timestamp is tz-aware and tz is not None.

        See Also
        --------
        Timestamp.tzinfo : Returns the timezone information of the Timestamp.
        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
        DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
        datetime.datetime.astimezone : Convert a datetime object to another time zone.

        Examples
        --------
        Create a naive timestamp object:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
        >>> ts
        Timestamp('2020-03-14 15:32:52.192548651')

        Add 'Europe/Stockholm' as timezone:

        >>> ts.tz_localize(tz='Europe/Stockholm')
        Timestamp('2020-03-14 15:32:52.192548651+0100', tz='Europe/Stockholm')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.tz_localize()
        NaT
        
        Convert timezone-aware Timestamp to another time zone.

        This method is used to convert a timezone-aware Timestamp object to a
        different time zone. The original UTC time remains the same; only the
        time zone information is changed. If the Timestamp is timezone-naive, a
        TypeError is raised.

        Parameters
        ----------
        tz : str, zoneinfo.ZoneInfo, pytz.timezone, dateutil.tz.tzfile or None
            Time zone for time which Timestamp will be converted to.
            None will remove timezone holding UTC time.

        Returns
        -------
        converted : Timestamp

        Raises
        ------
        TypeError
            If Timestamp is tz-naive.

        See Also
        --------
        Timestamp.tz_localize : Localize the Timestamp to a timezone.
        DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
        DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
        datetime.datetime.astimezone : Convert a datetime object to another time zone.

        Examples
        --------
        Create a timestamp object with UTC timezone:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651', tz='UTC')
        >>> ts
        Timestamp('2020-03-14 15:32:52.192548651+0000', tz='UTC')

        Change to Tokyo timezone:

        >>> ts.tz_convert(tz='Asia/Tokyo')
        Timestamp('2020-03-15 00:32:52.192548651+0900', tz='Asia/Tokyo')

        Can also use ``astimezone``:

        >>> ts.astimezone(tz='Asia/Tokyo')
        Timestamp('2020-03-15 00:32:52.192548651+0900', tz='Asia/Tokyo')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.tz_convert(tz='Asia/Tokyo')
        NaT
        
        Implements datetime.replace, handles nanoseconds.

        This method creates a new `Timestamp` object by replacing the specified
        fields with new values. The new `Timestamp` retains the original fields
        that are not explicitly replaced. This method handles nanoseconds, and
        the `tzinfo` parameter allows for timezone replacement without conversion.

        Parameters
        ----------
        year : int, optional
            The year to replace. If `None`, the year is not changed.
        month : int, optional
            The month to replace. If `None`, the month is not changed.
        day : int, optional
            The day to replace. If `None`, the day is not changed.
        hour : int, optional
            The hour to replace. If `None`, the hour is not changed.
        minute : int, optional
            The minute to replace. If `None`, the minute is not changed.
        second : int, optional
            The second to replace. If `None`, the second is not changed.
        microsecond : int, optional
            The microsecond to replace. If `None`, the microsecond is not changed.
        nanosecond : int, optional
            The nanosecond to replace. If `None`, the nanosecond is not changed.
        tzinfo : tz-convertible, optional
            The timezone information to replace. If `None`, the timezone is not changed.
        fold : int, optional
            The fold information to replace. If `None`, the fold is not changed.

        Returns
        -------
        Timestamp
            A new `Timestamp` object with the specified fields replaced.

        See Also
        --------
        Timestamp : Represents a single timestamp, similar to `datetime`.
        to_datetime : Converts various types of data to datetime.

        Notes
        -----
        The `replace` method does not perform timezone conversions. If you need
        to convert the timezone, use the `tz_convert` method instead.

        Examples
        --------
        Create a timestamp object:

        >>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651', tz='UTC')
        >>> ts
        Timestamp('2020-03-14 15:32:52.192548651+0000', tz='UTC')

        Replace year and the hour:

        >>> ts.replace(year=1999, hour=10)
        Timestamp('1999-03-14 10:32:52.192548651+0000', tz='UTC')

        Replace timezone (not a conversion):

        >>> import zoneinfo
        >>> ts.replace(tzinfo=zoneinfo.ZoneInfo('US/Pacific'))
        Timestamp('2020-03-14 15:32:52.192548651-0700', tz='US/Pacific')

        Analogous for ``pd.NaT``:

        >>> pd.NaT.replace(tzinfo=zoneinfo.ZoneInfo('US/Pacific'))
        NaT
         validate integers 
        Convert TimeStamp to a Julian Date.

        This method returns the number of days as a float since
        0 Julian date, which is noon January 1, 4713 BC.

        See Also
        --------
        Timestamp.toordinal : Return proleptic Gregorian ordinal.
        Timestamp.timestamp : Return POSIX timestamp as float.
        Timestamp : Represents a single timestamp.

        Examples
        --------
        >>> ts = pd.Timestamp('2020-03-14T15:32:52')
        >>> ts.to_julian_date()
        2458923.147824074
        
        Return the day of the week represented by the date.

        Monday == 1 ... Sunday == 7.

        See Also
        --------
        Timestamp.weekday : Return the day of the week with Monday=0, Sunday=6.
        Timestamp.isocalendar : Return a tuple containing ISO year, week number
            and weekday.
        datetime.date.isoweekday : Equivalent method in datetime module.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01 10:00:00')
        >>> ts
        Timestamp('2023-01-01 10:00:00')
        >>> ts.isoweekday()
        7
        
        Return the day of the week represented by the date.

        Monday == 0 ... Sunday == 6.

        See Also
        --------
        Timestamp.dayofweek : Return the day of the week with Monday=0, Sunday=6.
        Timestamp.isoweekday : Return the day of the week with Monday=1, Sunday=7.
        datetime.date.weekday : Equivalent method in datetime module.

        Examples
        --------
        >>> ts = pd.Timestamp('2023-01-01')
        >>> ts
        Timestamp('2023-01-01  00:00:00')
        >>> ts.weekday()
        6
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