+ Ŝiܣ a0t$^RIHt^RIHt^RIHt^RIHt^RI H t ^RI H t H t HtHtHtHt^RIt^RIt^RIHtHt^R IHtHtHtHtHtHtHtH t!^R I"H#t#^R I$H%t%H&t&^R I'H(t(^R I)H*t*H+t+H,t,^RI-H.t.^RI/H0t0^RI1H2t2H3t3H4t4H5t5H6t6H7t7H8t8^RI9H:t:H;t;^RIt>^RI?H@t@HAtAHBtB^RICHDtD^RIEHFtF^RIGHHtH^RIIHJtJHKtKHLtL^RIMHNtN^RIOHPtP^RIQHRtR] 'd#^RISHTtTHUtU^RIVHWtW^RIXHYtY^RI)HZtZ^RI[H\t\H]t]]^]_,]*,t`R ]aR!&]b]c,tdR ]aR"&]d],]P,tfR ]aR#&]f]`,tgR ]aR$&]^]d,]_]dR%3,,]*,thR ]aR&&!R'R(]R)R*7ti!R+R,]iR-R*7tj]]jR.3,tk^2tlReR/R0lltmRfR1R2lltnR3R4ltoRgR5R6lltpRhR7R8lltqRiR:R;lltrR<R=ltsR>R?lttR@tu]RjRARBll4tv]RjRCRDll4tv]RjRERFll4tv].!RG4R9R-R-R-R]PRRHR)3 RIRJll4tv/RKRKbRLRKbRMRMbRNRMbRORObRPRObRQRRbRSRRbRTRUbRVRUbRWRXbRYRXbRZRZbR[RZbR\RZbR]R]bR^R]bR_R]R`R`RaR`RbR`/CtxRcRdlty.RkOtzR#)l) annotations)abc)date)partial)islice) TYPE_CHECKING TypeAlias TypedDictUnioncastoverloadN)libtslib)NaTOutOfBoundsDatetime Timedelta Timestampastype_overflowsafeget_supported_dtypeis_supported_dtype timezones)cast_from_unit_vectorized)DateParseErrorguess_datetime_format)array_strptime) AnyArrayLike ArrayLikeDateTimeErrorChoices) set_module)find_stack_level) ensure_objectis_floatis_float_dtype is_integeris_integer_dtype is_list_likeis_numeric_dtype) ArrowDtypeDatetimeTZDtype) ABCDataFrame ABCSeries) DatetimeArray IntegerArrayNumpyExtensionArray)unique)ArrowExtensionArray)ExtensionArray)maybe_convert_dtypeobjects_to_datetime64 tz_to_dtype) extract_array)Index) DatetimeIndex)CallableHashable)NaTType) UnitChoices)TimeUnit) DataFrameSeriesr ArrayConvertibleScalarDatetimeScalar DatetimeScalarOrArrayConvertible.DatetimeDictArgc6]tRt^lt$R]R&R]R&R]R&RtR#)YearMonthDayDictrCyearmonthdayN__name__ __module__ __qualname____firstlineno____annotations____static_attributes__rId/Users/mibo/.openclaw/workspace/.venv-ak/lib/python3.14/site-packages/pandas/core/tools/datetimes.pyrErEls   rQrET)totalcr]tRt^rt$R]R&R]R&R]R&R]R&R]R&R]R&R]R&R]R &R]R &R tR #) FulldatetimeDictrChourhoursminuteminutessecondsecondsmsusnsrINrJrIrQrRrUrUrs8      rQrUFr=c V^8dQhRRRR/#)dayfirst bool | Nonereturn str | NonerI)formats"rR __annotate__rfsKJrQc,\P!V4;pR8wdw\W,;p4\Jd\\ W1R7pVeV#\P!W^,R4R8wd&\ P !R\\4R7R#)raNzCould not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.) stacklevel) rfirst_non_nulltypestrrwarningswarn UserWarningr )arrrarlfirst_non_nan_elementguessed_formats&& rR _guess_datetime_format_for_arrayrus..s33: )<<% = D2%N)%%##C(:(<$=>"D K /1  rQc(V^8dQhRRRRRRRR/#) r`argr? unique_sharefloat check_countz int | NonercboolrI)res"rRrfrfs,99 9).9CM9 9rQcRpVf=\V4\8:dR#\V4R8:d\V4^ ,pM3RpM0^Tu;8:d\V48:gQR4hQR4hV^8XdR#^Tu;8d^8gQR4hQR4h\\W44p\T4Y!,8dRpT# \dR#i;i)a Decides whether to do caching. If the percent of unique elements among `check_count` elements less than `unique_share * 100` then we can do caching. Parameters ---------- arg: listlike, tuple, 1-d array, Series unique_share: float, default=0.7, optional 0 < unique_share < 1 check_count: int, optional 0 <= check_count <= len(arg) Returns ------- do_caching: bool Notes ----- By default for a sequence of less than 50 items in size, we don't do caching; for the number of elements less than 5000, we take ten percent of all elements to check for a uniqueness share; if the sequence size is more than 5000, then we check only the first 500 elements. All constants were chosen empirically by. TFiiz1check_count must be in next bounds: [0; len(arg)]z+unique_share must be in next bounds: (0; 1))lenstart_caching_atsetr TypeError)rwrxrz do_cachingunique_elementss&&& rR should_cachers:J s8' ' s8t c(b.KKK+3s8+ ? + ? + !  | a N!NN N!NN fS67 ?k88  sC CCc ,V^8dQhRRRRRRRRR R /#) r`rwr?rerdcacher{convert_listliker8rcr>rI)res"rRrfrfs:// / / / /  /rQc^RIHpV!\R7pV'd\V4'gV#\ V\ P \\\34'g\ P!V4p\V4p\V4\V48dQV!Wa4pV!WvRR7pTPP'g"YUPP!4(,pV# \dTu#i;i)a Create a cache of unique dates from an array of dates Parameters ---------- arg : listlike, tuple, 1-d array, Series format : string Strftime format to parse time cache : bool True attempts to create a cache of converted values convert_listlike : function Conversion function to apply on dates Returns ------- cache_array : Series Cache of converted, unique dates. Can be empty r>dtypeF)indexcopy)pandasr>objectr isinstancenpndarrayr1r6r+arrayr/r}rr is_unique duplicated)rwrerrr> cache_array unique_dates cache_datess&&&& rR _maybe_cachers0v&K C   # NE9MNN((3-Cc{ | s3x '*<@K #$[5Q $$...)+<+<+G+G+I*IJ  ' #"" #s" C++ C;:C;c(V^8dQhRRRRRRRR/#) r`dt_arrayrutcr{nameHashable | Nonercr6rI)res"rRrfrf s,<<<"<2A< rrrcr6rI)res"rRrfrf's6CC )CC C CrQc^RIHpV!WPPR7P V4p\ VP RVR7#)aO Convert array of dates with a cache and wrap the result in an Index. Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series cache_array : Series Cache of converted, unique dates name : string, default None Name for a DatetimeIndex Returns ------- result : Index-like of converted dates rrFrr)rr>rrmapr_values)rwrrr>results&&& rR_convert_and_box_cacher's;( C0066 7 ; ;K HF V^^T BBrQraisec8V^8dQhRRRRRRRRRR R R R R R R/#)r`rerdrrrr{uniterrorsrrarb yearfirstexactrI)res"rRrfrfAsdG9G9 G9 G9  G9  G9 ! G9G9G9 G9rQc 4\V\\34'd\P!VRR7pM,\V\ 4'd\P!V4p\ VRR4p V'dRMRp \V \4'dT\V\\34'g\W VR7#V'd!VPR4PR4pV#\V \4'dV P\JdV'd\V\4'de\!\"VP4p V P$P&eV P)R4p MV P+R4p \V RR 7pV#V P$P&eVP)R4pV#VP+R4pV#\,P.!V R 4'd\1V 4'g:\3\P4!V4\P6!R 4VR 8HR 7p\V\\34'g\W VR7#V'dVPR4#V#VeVe \9R4h\;WW#V4#\ VR^4^8d \=R4h\?VR\@PB!V 4R7wr \KT4pTf \MYR7pTeTR8wd\OYY1Y4#\QTTTTTRR7wrTe\PR!TP64^,p\!RT4p\UTT4pTPWRTPX R24p\PZ!TTR7p\PZ!TTR7#\]YTR7# \<dMTR 8XdD\PD!\GT4\PH!RR44p \YR7u#hi;i)a Helper function for to_datetime. Performs the conversions of 1D listlike of dates Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be parsed name : object None or string for the Index name utc : bool Whether to convert/localize timestamps to UTC. unit : str None or string of the frequency of the passed data errors : str error handing behaviors from to_datetime, 'raise', 'coerce' dayfirst : bool dayfirst parsing behavior from to_datetime yearfirst : bool yearfirst parsing behavior from to_datetime exact : bool, default True exact format matching behavior from to_datetime Returns ------- Index-like of parsed dates OrrNrrUTCFrrzM8[s]coerce) is_coercez#cannot specify both format and unitndimzAarg must be a string, datetime, list, tuple, 1-d array, or Series)rrrr^rrimixedT)rarrr allow_objectr<M8[]r)/rlisttuplerrr.getattrr)r,r7 tz_convert tz_localizer(rmrr6r r0 pyarrow_dtyper_dt_tz_convert_dt_tz_localizerrrrasarrayr ValueError_to_datetime_with_unitrr2 libtimezones maybe_get_tzfullr} datetime64r!ru_array_strptime_with_fallbackr3 datetime_datar4viewr _simple_newr)rwrerrrrrarr arg_dtyper arg_array_npvaluesr tz_parsedout_unitr dt64_valuesdtas&&&&&&&&& rR_convert_listlike_datetimesrAsrL#e}%%hhs#& C, - -hhsmWd+I4B)_--# }=>> $7 7 ..&2259C Iz * *y~~/J #u%% !4cii@ **--9 ) 8 8 ?I ) 9 9% @IIE2  ((++7((/ ))%0 C ( (!),,% 3! H,C # }=>> $7 7 ??5) )   BC C%cFCC fa 1 $ O  $Su9R9RSU9VW  C ~1#If/,SUSS-   F##FLL1!4 H-Ix0kkC |1"56 '' 5A((488 V4 88E  X wws3xud)CDH 5 5 s7$OAPPc ,V^8dQhRRRRRRRRRR/#) r`rr{fmtrnrrrcr6rI)res"rRrfrfsEDD D D  D  D DrQc\WWEVR7wrgVe}\P!VP4^,p\ RV4p\ WxR7p \ P!WiR7p V'dV PR4p \WRR7#VP\8wdQV'dI\P!VP4^,p\ RV4p\VRV R 2VRR 7p V #\WfPVRR 7#) zD Call array_strptime, with fallback behavior depending on 'errors'. )rrrr<)rrrrF)rrrz, UTC])rrr) rrrrr r)r,rrr6r) rwrrrrrrtz_outrrrress &&&&&& rRrrs$CEcRNF  -a0J%65''< ..'CS%00  C -a0J%FCvV"44eL ||$U CCrQc$V^8dQhRRRRRR/#)r`rr{rrnrcr6rI)res"rRrfrfs&MMMsMuMrQc >\VRR7p\V\4'dVPRV R24pRpEM\P !V4pVP PR9d?VPRV R2RR7p\VP 4p\WWRR7pRpEM7VP PR 8Xd\P!R R 7;_uu_4VP\P4pRRR4\P!V4p WX8H,P!4'd$\WW#VR 7p \"V P$V &V #\P!R R7;_uu_4\'WR7pRRR4XP)R4pRpM3VP\RR7p\*P,!VVVVR7wrV\/WRR7p \V \.4'gV #V P1R4P3V4p V'd3V P4fV P1R4p V #V P3R4p V # \d.TR 8XdhTP\4p\YY#T4u#i;i +'giEL;i \dLp TR 8wd0\TP\4YY44uRp ? uuRRR4#\RT R24T hRp ? ii;i +'giEL;i)z> to_datetime specalized to the case where a 'unit' is passed. T) extract_numpyz datetime64[rNiuFrrfignore)invalid)rrrr)overrz cannot convert input with unit ''zM8[ns])rrunit_for_numericsrrr)r5rr-astyperrrkindrrrrrerrstateint64isnanallr_datarrrarray_to_datetimer7rrr) rwrrrrrrrr int_valuesmaskrerrs &&&&& rRrrs 4 0C#|$$jj;tfA./ jjo 99>>T !**{4&2*?C' 2E L)#5A I YY^^s "X.. ZZ1 /88C=Dz)*//110f&) T" '** 3CCC+((8$CI**V%*0C"44"& NC3 *F fm , ,    & 1 1) H>' H>4 H> H;* H66H;> I< I I<&I<'I77I<c@V^8dQhRRRRRRRRRRR R R RR R R RRR/ #)r`rwrArrrar{rrrerdrrrrcrrI)res"rRrfrfsl                   rQc R#NrI rwrrarrrerrrrs &&&&&&&&&&rR to_datetimersrQc@V^8dQhRRRRRRRRRRR R R RR R R RRR/ #)r`rwzSeries | DictConvertiblerrrar{rrrerdrrrrcr>rI)res"rRrfrfsl   !                 rQc R#rrIrs &&&&&&&&&&rRrrsrQc@V^8dQhRRRRRRRRRRR R R RR R R RRR/ #)r`rwz list | tuple | Index | ArrayLikerrrar{rrrerdrrrrcr7rI)res"rRrfrfsl   )                rQc R#rrIrs &&&&&&&&&&rRrrsrQrunixcDV^8dQhRRRRRRRRRRR R R R R R RRRRRR/ #)r`rwz2DatetimeScalarOrArrayConvertible | DictConvertiblerrrar{rrrerdrzbool | lib.NoDefaultrrrnrrcz1DatetimeIndex | Series | DatetimeScalar | NaTTyperI)res"rRrfrfsII ;I II I  I  I I I I I7IrQc V\PJdVR 9d \R4hVf\#VR8wd \ WV4p\ \ VVVVVVR7p \V\4'd?Tp V'd3VPeVPR4p V #VPR4p V #\V\4'do\WW4p V P'gVPV 4p V #V !VP V4p VP#WP$VP&R7p V #\V\(\*P,34'd\/WV4p V #\V\04'dO\WW4p V P'g\3W VP&R7p V #V !WVP&R7p V #\5V4'du\7\8\:\<\>\@PBR\03,V4p\WW4p V P'g\3XV 4p V #V !XV4p V #V !\@PL!V.4V4^,p \V\N4'd,\V \@PP4'd \OV 4p V # \Dd TR8Xdh^R I#H$pT!.\JR 7p Li;i) a1 Convert argument to datetime. This function converts a scalar, array-like, :class:`Series` or :class:`DataFrame`/dict-like to a pandas datetime object. Parameters ---------- arg : int, float, str, datetime, list, tuple, 1-d array, Series, DataFrame/dict-like The object to convert to a datetime. If a :class:`DataFrame` is provided, the method expects minimally the following columns: :const:`"year"`, :const:`"month"`, :const:`"day"`. The column "year" must be specified in 4-digit format. errors : {'raise', 'coerce'}, default 'raise' - If :const:`'raise'`, then invalid parsing will raise an exception. - If :const:`'coerce'`, then invalid parsing will be set as :const:`NaT`. dayfirst : bool, default False Specify a date parse order if `arg` is str or is list-like. If :const:`True`, parses dates with the day first, e.g. :const:`"10/11/12"` is parsed as :const:`2012-11-10`. .. warning:: ``dayfirst=True`` is not strict, but will prefer to parse with day first. yearfirst : bool, default False Specify a date parse order if `arg` is str or is list-like. - If :const:`True` parses dates with the year first, e.g. :const:`"10/11/12"` is parsed as :const:`2010-11-12`. - If both `dayfirst` and `yearfirst` are :const:`True`, `yearfirst` is preceded (same as :mod:`dateutil`). .. warning:: ``yearfirst=True`` is not strict, but will prefer to parse with year first. utc : bool, default False Control timezone-related parsing, localization and conversion. - If :const:`True`, the function *always* returns a timezone-aware UTC-localized :class:`Timestamp`, :class:`Series` or :class:`DatetimeIndex`. To do this, timezone-naive inputs are *localized* as UTC, while timezone-aware inputs are *converted* to UTC. - If :const:`False` (default), inputs will not be coerced to UTC. Timezone-naive inputs will remain naive, while timezone-aware ones will keep their time offsets. Limitations exist for mixed offsets (typically, daylight savings), see :ref:`Examples ` section for details. See also: pandas general documentation about `timezone conversion and localization `_. format : str, default None The strftime to parse time, e.g. :const:`"%d/%m/%Y"`. See `strftime documentation `_ for more information on choices, though note that :const:`"%f"` will parse all the way up to nanoseconds. You can also pass: - "ISO8601", to parse any `ISO8601 `_ time string (not necessarily in exactly the same format); - "mixed", to infer the format for each element individually. This is risky, and you should probably use it along with `dayfirst`. .. note:: If a :class:`DataFrame` is passed, then `format` has no effect. exact : bool, default True Control how `format` is used: - If :const:`True`, require an exact `format` match. - If :const:`False`, allow the `format` to match anywhere in the target string. Cannot be used alongside ``format='ISO8601'`` or ``format='mixed'``. unit : str, default 'ns' The unit of the arg (D,s,ms,us,ns) denote the unit, which is an integer or float number. This will be based off the origin. Example, with ``unit='ms'`` and ``origin='unix'``, this would calculate the number of milliseconds to the unix epoch start. origin : scalar, default 'unix' Define the reference date. The numeric values would be parsed as number of units (defined by `unit`) since this reference date. - If :const:`'unix'` (or POSIX) time; origin is set to 1970-01-01. - If :const:`'julian'`, unit must be :const:`'D'`, and origin is set to beginning of Julian Calendar. Julian day number :const:`0` is assigned to the day starting at noon on January 1, 4713 BC. - If Timestamp convertible (Timestamp, dt.datetime, np.datetimt64 or date string), origin is set to Timestamp identified by origin. - If a float or integer, origin is the difference (in units determined by the ``unit`` argument) relative to 1970-01-01. cache : bool, default True If :const:`True`, use a cache of unique, converted dates to apply the datetime conversion. May produce significant speed-up when parsing duplicate date strings, especially ones with timezone offsets. The cache is only used when there are at least 50 values. The presence of out-of-bounds values will render the cache unusable and may slow down parsing. Returns ------- datetime If parsing succeeded. Return type depends on input (types in parenthesis correspond to fallback in case of unsuccessful timezone or out-of-range timestamp parsing): - scalar: :class:`Timestamp` (or :class:`datetime.datetime`) - array-like: :class:`DatetimeIndex` (or :class:`Series` with :class:`object` dtype containing :class:`datetime.datetime`) - Series: :class:`Series` of :class:`datetime64` dtype (or :class:`Series` of :class:`object` dtype containing :class:`datetime.datetime`) - DataFrame: :class:`Series` of :class:`datetime64` dtype (or :class:`Series` of :class:`object` dtype containing :class:`datetime.datetime`) Raises ------ ParserError When parsing a date from string fails. ValueError When another datetime conversion error happens. For example when one of 'year', 'month', day' columns is missing in a :class:`DataFrame`, or when a Timezone-aware :class:`datetime.datetime` is found in an array-like of mixed time offsets, and ``utc=False``, or when parsing datetimes with mixed time zones unless ``utc=True``. If parsing datetimes with mixed time zones, please specify ``utc=True``. See Also -------- DataFrame.astype : Cast argument to a specified dtype. to_timedelta : Convert argument to timedelta. convert_dtypes : Convert dtypes. Notes ----- Many input types are supported, and lead to different output types: - **scalars** can be int, float, str, datetime object (from stdlib :mod:`datetime` module or :mod:`numpy`). They are converted to :class:`Timestamp` when possible, otherwise they are converted to :class:`datetime.datetime`. None/NaN/null scalars are converted to :const:`NaT`. - **array-like** can contain int, float, str, datetime objects. They are converted to :class:`DatetimeIndex` when possible, otherwise they are converted to :class:`Index` with :class:`object` dtype, containing :class:`datetime.datetime`. None/NaN/null entries are converted to :const:`NaT` in both cases. - **Series** are converted to :class:`Series` with :class:`datetime64` dtype when possible, otherwise they are converted to :class:`Series` with :class:`object` dtype, containing :class:`datetime.datetime`. None/NaN/null entries are converted to :const:`NaT` in both cases. - **DataFrame/dict-like** are converted to :class:`Series` with :class:`datetime64` dtype. For each row a datetime is created from assembling the various dataframe columns. Column keys can be common abbreviations like ['year', 'month', 'day', 'minute', 'second', 'ms', 'us', 'ns']) or plurals of the same. The following causes are responsible for :class:`datetime.datetime` objects being returned (possibly inside an :class:`Index` or a :class:`Series` with :class:`object` dtype) instead of a proper pandas designated type (:class:`Timestamp`, :class:`DatetimeIndex` or :class:`Series` with :class:`datetime64` dtype): - when any input element is before :const:`Timestamp.min` or after :const:`Timestamp.max`, see `timestamp limitations `_. - when ``utc=False`` (default) and the input is an array-like or :class:`Series` containing mixed naive/aware datetime, or aware with mixed time offsets. Note that this happens in the (quite frequent) situation when the timezone has a daylight savings policy. In that case you may wish to use ``utc=True``. Examples -------- **Handling various input formats** Assembling a datetime from multiple columns of a :class:`DataFrame`. The keys can be common abbreviations like ['year', 'month', 'day', 'minute', 'second', 'ms', 'us', 'ns']) or plurals of the same >>> df = pd.DataFrame({"year": [2015, 2016], "month": [2, 3], "day": [4, 5]}) >>> pd.to_datetime(df) 0 2015-02-04 1 2016-03-05 dtype: datetime64[us] Using a unix epoch time >>> pd.to_datetime(1490195805, unit="s") Timestamp('2017-03-22 15:16:45') >>> pd.to_datetime(1490195805433502912, unit="ns") Timestamp('2017-03-22 15:16:45.433502912') .. warning:: For float arg, precision rounding might happen. To prevent unexpected behavior use a fixed-width exact type. Using a non-unix epoch origin >>> pd.to_datetime([1, 2, 3], unit="D", origin=pd.Timestamp("1960-01-01")) DatetimeIndex(['1960-01-02', '1960-01-03', '1960-01-04'], dtype='datetime64[s]', freq=None) **Differences with strptime behavior** :const:`"%f"` will parse all the way up to nanoseconds. >>> pd.to_datetime("2018-10-26 12:00:00.0000000011", format="%Y-%m-%d %H:%M:%S.%f") Timestamp('2018-10-26 12:00:00.000000001') **Non-convertible date/times** Passing ``errors='coerce'`` will force an out-of-bounds date to :const:`NaT`, in addition to forcing non-dates (or non-parseable dates) to :const:`NaT`. >>> pd.to_datetime("invalid for Ymd", format="%Y%m%d", errors="coerce") NaT .. _to_datetime_tz_examples: **Timezones and time offsets** The default behaviour (``utc=False``) is as follows: - Timezone-naive inputs are converted to timezone-naive :class:`DatetimeIndex`: >>> pd.to_datetime(["2018-10-26 12:00:00", "2018-10-26 13:00:15"]) DatetimeIndex(['2018-10-26 12:00:00', '2018-10-26 13:00:15'], dtype='datetime64[us]', freq=None) - Timezone-aware inputs *with constant time offset* are converted to timezone-aware :class:`DatetimeIndex`: >>> pd.to_datetime(["2018-10-26 12:00 -0500", "2018-10-26 13:00 -0500"]) DatetimeIndex(['2018-10-26 12:00:00-05:00', '2018-10-26 13:00:00-05:00'], dtype='datetime64[us, UTC-05:00]', freq=None) - However, timezone-aware inputs *with mixed time offsets* (for example issued from a timezone with daylight savings, such as Europe/Paris) are **not successfully converted** to a :class:`DatetimeIndex`. Parsing datetimes with mixed time zones will raise a ValueError unless ``utc=True``: >>> pd.to_datetime( ... ["2020-10-25 02:00 +0200", "2020-10-25 04:00 +0100"] ... ) # doctest: +SKIP ValueError: Mixed timezones detected. Pass utc=True in to_datetime or tz='UTC' in DatetimeIndex to convert to a common timezone. - To create a :class:`Series` with mixed offsets and ``object`` dtype, please use :meth:`Series.apply` and :func:`datetime.datetime.strptime`: >>> import datetime as dt >>> ser = pd.Series(["2020-10-25 02:00 +0200", "2020-10-25 04:00 +0100"]) >>> ser.apply(lambda x: dt.datetime.strptime(x, "%Y-%m-%d %H:%M %z")) 0 2020-10-25 02:00:00+02:00 1 2020-10-25 04:00:00+01:00 dtype: object - A mix of timezone-aware and timezone-naive inputs will also raise a ValueError unless ``utc=True``: >>> from datetime import datetime >>> pd.to_datetime( ... ["2020-01-01 01:00:00-01:00", datetime(2020, 1, 1, 3, 0)] ... ) # doctest: +SKIP ValueError: Mixed timezones detected. Pass utc=True in to_datetime or tz='UTC' in DatetimeIndex to convert to a common timezone. | Setting ``utc=True`` solves most of the above issues: - Timezone-naive inputs are *localized* as UTC >>> pd.to_datetime(["2018-10-26 12:00", "2018-10-26 13:00"], utc=True) DatetimeIndex(['2018-10-26 12:00:00+00:00', '2018-10-26 13:00:00+00:00'], dtype='datetime64[us, UTC]', freq=None) - Timezone-aware inputs are *converted* to UTC (the output represents the exact same datetime, but viewed from the UTC time offset `+00:00`). >>> pd.to_datetime(["2018-10-26 12:00 -0530", "2018-10-26 12:00 -0500"], utc=True) DatetimeIndex(['2018-10-26 17:30:00+00:00', '2018-10-26 17:00:00+00:00'], dtype='datetime64[us, UTC]', freq=None) - Inputs can contain both string or datetime, the above rules still apply >>> pd.to_datetime(["2018-10-26 12:00", datetime(2020, 1, 1, 18)], utc=True) DatetimeIndex(['2018-10-26 12:00:00+00:00', '2020-01-01 18:00:00+00:00'], dtype='datetime64[us, UTC]', freq=None) z8Cannot use 'exact' when 'format' is 'mixed' or 'ISO8601'r )rrrarrrr)rrrr>rrr>rISO8601))r no_defaultrrrrrrrrrrr+remptyrr _constructorrrr*rMutableMapping_assemble_from_unit_mappingsr6rr&r r rrr1rrrrr>rrr{bool_)rwrrarrrerrrrrrrvaluesargcr>s&&&&&&&&&& rRrrsD  CNN"v1E'ESTT {  T2#  #y!! vv!.b M_/^ M] C # #"3H    WW[)FV MS&ckk6:F%%fIICHH%MFP MO C,(:(:; < <-c3?L MK C  "3H    +C388LFD MA&cAF@ M? c   3 dE>2::xNOQTD'tUMK   +D+>F M&dF3F M""((C5/6:1= c4 Z%A%A&\F M+# 3  % 62K 3sAJ77'K! K!rFyearsrGmonthsrHdaysrVhrWrXmrYrZsr[r\ millisecond millisecondsr] microsecond microsecondsr^ nanosecond nanosecondsc$V^8dQhRRRRRR/#)r`rrrr{rcr>rI)res"rRrfrfVs)``%`,0` `rQcaa^RIHpHoHpV!V4pVPP 'g \ R4hRpVP4Uu/uF qfV!V4bK ppVP4UUu/uFwrhWbK p pp.ROp \V 4\V P44, p \V 4'd*RP\V 44p \ RV R 24h\V P44\\P44, p \V 4'd*RP\V 44p\ R V R 24hVV3R lpV!W R,,4R ,V!W R,,4^d,,V!W R,,4,p\VRSVR7p.ROpTFCpT P#T4pTfKTT9gK#TT!T!TT,4TSR7, pKE T#uupiuuppi \ \ 3dp\ RT 24ThRp?ii;i \ \ 3dp\ RT RT 24ThRp?ii;i)a assemble the unit specified fields from the arg (DataFrame) Return a Series for actual parsing Parameters ---------- arg : DataFrame errors : {'raise', 'coerce'}, default 'raise' - If :const:`'raise'`, then invalid parsing will raise an exception - If :const:`'coerce'`, then invalid parsing will be set as :const:`NaT` utc : bool Whether to convert/localize timestamps to UTC. Returns ------- Series )r= to_numeric to_timedeltaz#cannot assemble with duplicate keyscV\9d\V,#VP4\9d\VP4,#V#r) _unit_maplower)values&rRr'_assemble_from_unit_mappings..fvs; I U# # ;;=I %U[[]+ + rQrFrGrH,zNto assemble mappings requires at least that [year, month, day] be specified: [z ] is missingz9extra keys have been passed to the datetime assemblage: [rc<S!VSR7p\VP4'dVPR4p\VP4'dVPR4pV#))rfloat64r)r#rrr%)rrr's&rRr,_assemble_from_unit_mappings..coercesRF62 &,, ' ']]9-F FLL ) )]]7+F rQi'z%Y%m%d)rerrzcannot assemble the datetimes: N)rrzcannot assemble the datetimes [z]: )rFrGrH)rrrr\r]r^)rr=r'r(columnsrrkeysitemsrr}joinsortedr*rrrget)rwrrr=r(rkrvunit_revrequiredreq _requiredexcess_excessrrrunitsur,r's&f& @rRrrVsS* C.C ;; >??!XXZ (ZqtGZD (!%.H.(H h-#hmmo. .C 3xxHHVC[)  11: < I   !C (8(8(:$; ;F 6{{((6&>*GyPQ R    sF#$%- g&' (3 . / e_% & ' KVHVM AE  Q  # ,vc%j'9&QQ  Mm ).P z "K:3%@AsJKz*  5eWCuE s<H 7 H%H+;I+I<I  II;$I66I;)F)gffffff?N)FNr)NFNrNNT) .........)rrr){__conditional_annotations__ __future__r collectionsrdatetimer functoolsr itertoolsrtypingrr r r r r ronumpyr pandas._libsrrpandas._libs.tslibsrrrrrrrrrpandas._libs.tslibs.conversionrpandas._libs.tslibs.parsingrrpandas._libs.tslibs.strptimerpandas._typingrrrpandas.util._decoratorsrpandas.util._exceptionsr pandas.core.dtypes.commonr!r"r#r$r%r&r'pandas.core.dtypes.dtypesr(r)pandas.core.dtypes.genericr*r+ pandas.arraysr,r-r.pandas.core.algorithmsr/pandas.core.arraysr0pandas.core.arrays.baser1pandas.core.arrays.datetimesr2r3r4pandas.core.constructionr5pandas.core.indexes.baser6pandas.core.indexes.datetimesr7collections.abcr8r9pandas._libs.tslibs.nattyper:pandas._libs.tslibs.timedeltasr;r<rr=r>rrr?rOryrnr@rrArBrCrErUDictConvertibler~rurrrrrrrrrrr*r__all__)rBs@rRrbs""   E8 /4  *22 3*7 4:'#Ul\9)9CK "TMBMM9 9.>MMy 'u (+56 .9x/d<:C4G9TD8M`HV             H$+"%..IIZ   F  V  W  g    5    E   C  S  c s  c s  $ 4 D   $! 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