!h bddlmZddlmZddlmZddlmZddlm Z ddl m Z m Z m Z mZmZmZddlZddlZddlmZmZdd lmZmZmZmZmZmZdd lm Z dd l!m"Z"m#Z#dd l$m%Z%dd l&m'Z'm(Z(m)Z)ddl*m+Z+ddl,m-Z-m.Z.m/Z/m0Z0m1Z1m2Z2ddl3m4Z4m5Z5ddl6m7Z7m8Z8ddl9m:Z:m;Z;mZ>ddl?m@Z@ddlAmBZBddlCmDZDmEZEmFZFddlGmHZHddlImJZJddlKmLZLe rddlMmNZNddlOmPZPddlQmRZRddlSmTZTmUZUeeVeWe'fZXeeYeZfZ[ee[eej\fZ]ee]eXfZ^eeVe[eWe[dfe'fZ_Gdd e d!"Z`Gd#d$e`d%"Zaeead&fZbd'Zcdzd{d,Zd d|d}d5Zed~d;Zf dddBZg dddEZh dddLZiddOZjddPZkdQZle dddUZme dddWZme dddZZmdFd%d%d%dejndejnd[d!f ddaZmidbdbdcdbdddddedddfdfdgdfdhdidjdidkdldmdldndodpdodqdqdrdqdsdqdtdtdudtdtdvdvdvdwZoddxZpgdyZqdS)) annotations)abc)date)partial)islice) TYPE_CHECKINGCallable TypedDictUnioncastoverloadN)libtslib)OutOfBoundsDatetime Timedelta Timestampastype_overflowsafeis_supported_dtype timezones)cast_from_unit_vectorized)DateParseErrorguess_datetime_format)array_strptime) AnyArrayLike ArrayLikeDateTimeErrorChoices)find_stack_level) ensure_objectis_float 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)Hashable)NaTType) UnitChoices) DataFrameSeries.c.eZdZUded<ded<ded<dS)YearMonthDayDictDatetimeDictArgyearmonthdayN__name__ __module__ __qualname____annotations__Uc:\xampp_lite_8_4\www\timesheet\venv\Lib\site-packages\pandas/core/tools/datetimes.pyr:r:es6rEr:T)totalcjeZdZUded<ded<ded<ded<ded<ded<ded<ded <ded <d S) FulldatetimeDictr;hourhoursminuteminutessecondsecondsmsusnsNr?rDrErFrIrIks~rErIFr72dayfirst bool | Nonereturn str | Nonec6tj|x}dkr~t||x}tur`t ||}||Stj||dzddkr(t jdttdS)NrTzCould 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)arrrTr^first_non_nan_elementguessed_formats rF _guess_datetime_format_for_arrayrg~s.s333:: ^)<<% = = D D2%N)%%#C(:(<(<$=>>"DD K /11  4rEffffff?argArrayConvertible unique_sharefloat check_count int | Noneboolcd}|Ct|tkrdSt|dkrt|dz}n1d}n.d|cxkrt|ks nJd|dkrdSd|cxkrd ks nJd  tt||}n#t$rYdSwxYwt|||zkrd}|S) 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. TNFi irz1check_count must be in next bounds: [0; len(arg)]r[z+unique_share must be in next bounds: (0; 1))lenstart_caching_atsetr TypeError)rirkrm do_cachingunique_elementss rF should_cacherxs*:J s88' ' '5 s88t  c((b.KKKK  ( ( ( (C ( ( ( ( ( > ) ( ( !  5 |    a     !N   fS+6677 uu ?kL888 sB.. B<;B<formatcacheconvert_listliker r8cddlm}|t}|rt|s|St |t jtttfst j |}t|}t|t|krZ|||} |||d}n#t$r|cYSwxYw|jjs ||j}|S)a Create a cache of unique dates from an array of dates Parameters ---------- arg : listlike, tuple, 1-d array, Series format : string Strftime format to parse time cache : bool True attempts to create a cache of converted values convert_listlike : function Conversion function to apply on dates Returns ------- cache_array : Series Cache of converted, unique dates. Can be empty rr8dtypeF)indexcopy)pandasr8objectrx isinstancenpndarrayr-r2r'arrayr+rrrr is_unique duplicated)riryrzr{r8 cache_array unique_dates cache_datess rF _maybe_cachers0&v&&&K KC    # NE9MNN (3--Cc{{ |  s3xx ' '**<@@K #$f[ 5QQQ & # # #"""" #$. K);+<+G+G+I+I*IJ s(B77 CCdt_arrayrutcnameHashable | Noner2ctj|jdr|rdnd}t|||St |||jS)a  Properly boxes the ndarray of datetimes to DatetimeIndex if it is possible or to generic Index instead Parameters ---------- dt_array: 1-d array Array of datetimes to be wrapped in an Index. utc : bool Whether to convert/localize timestamps to UTC. name : string, default None Name for a resulting index Returns ------- result : datetime of converted dates - DatetimeIndex if convertible to sole datetime64 type - general Index otherwise MrNtzr)rr)r is_np_dtyperr3r2)rrrrs rF_box_as_indexlikersT. x~s++9 #UUtX"48888 HN ; ; ;;rE DatetimeScalarOrArrayConvertiblercddlm}|||jj|}t |jd|S)a Convert array of dates with a cache and wrap the result in an Index. Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series cache_array : Series Cache of converted, unique dates name : string, default None Name for a DatetimeIndex Returns ------- result : Index-like of converted dates rr}r~Frr)rr8rrmapr_values)rirrr8results rF_convert_and_box_cacher sU( VC{06 7 7 7 ; ;K H HF V^T B B BBrEraiseuniterrorsr yearfirstexactc ~t|ttfrtj|d}n)t|t rtj|}t |dd} |rdnd} t| trZt|ttfst|| |S|r(| d d}|St| tr| j tur|rt|trat!t"|j} | jj| d} n| d} t| }n7| jj|d}n|d}|St-j| drt1| s:t3tj|tjd |d k }t|ttfst|| |S|r| dS|S|$|t9d t;|||||St |d ddkrt=d t?|dtAj!| \}} nz#t<$rm|d krJtjdgd"tG|} t| |cYS|dkrt||}|cYSwxYwtI|}|tK||}||dkrtM||||||StO|||||d\}}|tj(|jd}t!ttS||}|*d|j+d}tj,||}tj,||St[|||S)a Helper function for to_datetime. Performs the conversions of 1D listlike of dates Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be parsed name : object None or string for the Index name utc : bool Whether to convert/localize timestamps to UTC. unit : str None or string of the frequency of the passed data errors : str error handing behaviors from to_datetime, 'raise', 'coerce', 'ignore' dayfirst : bool dayfirst parsing behavior from to_datetime yearfirst : bool yearfirst parsing behavior from to_datetime exact : bool, default True exact format matching behavior from to_datetime Returns ------- Index-like of parsed dates Or~rNrrUTCrzM8[s]coerce) is_coercez#cannot specify both format and unitndimr[zAarg must be a string, datetime, list, tuple, 1-d array, or SeriesF)rrNaTzdatetime64[ns]rignorerZmixedT)rTrrr allow_objectrM8[]r).rlisttuplerrr*getattrr%r(r3 tz_convert tz_localizer$r_rr2r r, pyarrow_dtyper_dt_tz_convert_dt_tz_localizerrrrasarrayr ValueError_to_datetime_with_unitrur. libtimezones maybe_get_tzrepeatrrrrg_array_strptime_with_fallbackr/ datetime_datar0viewr _simple_newr)riryrrrrrTrr arg_dtyper arg_array_npvaluesidxr tz_parsedout_unitr dt64_valuesdtas rF_convert_listlike_datetimesr:svL#e}%%hs#&&& C, - -hsmmWd++I 4B)_--3 # }=>> 8 $777 7  :..&&22599C Iz * *, y~/J/J  5#u%% 5 !4ci@@ *-9 ) 8 8 ? ?II ) 9 9% @ @II&&*-9,,U33CC--e44C C ( ( !),, % 3!! H, C# }=>> * $777 7  *??5)) )   BCC C%c4sFCCC fa 1 $ $ O   $Su9RSU9V9VWWWQQ  X  x/?@@@GGCQQH 555 5 5 5 x  $'''CJJJ    C ~1#IIIf//,S$VUFSSS-   FI#FL11!4_k)X&F&FGGkk"5 "5"5"566 ' 5AAA(48888 V4 8 8 88s''KAM)MMfmtr`ct|||||\}}|ntj|jd}t ||} t j|| } |r| d} t| |S|jtkr9|r7tj|jd}t|d|d | } | St||j| S) zL Call array_strptime, with fallback behavior depending on 'errors'. )rrrNr)rrr~rrrz, UTC])rr) rrrrr%r(rrr2r) rirrrrrrtz_outrrrress rFrrs$CE&cRRRNFF  --a06555'e<<<  (..''CSt$$$$   C  --a0F"4"4"4"44@@@ v|$ 7 7 77rEc  t|d}t|tr|d|d}d}nt j|}|jjdvr|d|dd} t|t jd d}nD#t$r7|d kr|t}t|||||cYSwxYwd}n|jjd krt j d 5 t|| }n`#t$rS|d kr9t|t||||cYcdddStd|dwxYw dddn #1swxYwY|d }d}n6|td}tj|||\}}|dkrt#j||}nt'||}t|t&s|S|d|}|r2|j|d}n|d}|S)zF to_datetime specalized to the case where a 'unit' is passed. T) extract_numpyz datetime64[rNiuFrzM8[ns]rf)overrz cannot convert input with unit ''rrrrr)r1rr)astyperrrkindrrrrerrstaterrrarray_with_unit_to_datetimer2 _with_inferr3rrr)rirrrrrdrrs rFrrs@ 4 0 0 0C#|$$$Yjj.t...// joo 9>T ! !**24222*??C L)#rx/A/ANNN& L L LW$$jj((-c4sFKKKKK  L II Y^s " "'***   3CdCCCCC*((5JJv..dC          .B4BBB                ((8$$CII**V%*00C">sDQWXXXNC "3T222s... fm , ,    & & 1 1) < C('C(FD'&F';F"F0FFFFc\|dkr|}td}|dkrtd ||z }n"#t$r}td|d}~wwxYwtj|z }tj|z }t j||kst j||krt|dn>t|sFt|s7tt j |std|d |d  t|| }nG#t$r}td |d |d}~wt$r}td |d|d}~wwxYw|j td|d|tdz } | td| z} t|r;t!|t"t$t jfst j |}|| z}|S)a Helper function for to_datetime. Adjust input argument to the specified origin Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be adjusted origin : 'julian' or Timestamp origin offset for the arg unit : str passed unit from to_datetime, must be 'D' Returns ------- ndarray or scalar of adjusted date(s) julianrDz$unit must be 'D' for origin='julian'z3incompatible 'arg' type for given 'origin'='julian'Nz% is Out of Bounds for origin='julian'rz!' is not compatible with origin='z+'; it must be numeric with a unit specifiedrzorigin z is Out of Boundsz# cannot be converted to a Timestampzorigin offset z must be tz-naiver[)rto_julian_daterrumaxminranyrr rr#rrrr"rr'r2r) rioriginroriginalj0errj_maxj_minoffset td_offsetioffsets rF_adjust_to_originr&s$ q\\ ( ( * * 3;;CDD D (CC   E    ,,..3 ,,..3 6#+   "&u"5"5 %BBB  __  (  2B2:c??2S2S ;C;;&;;;   vD111FF" T T T%&I&I&I&IJJPS S   E&EEE   9 GfGGGHH HYq\\) y6666    "Zi 5S%T%T "*S//CGm Js<A A%A  A%E F E44 FFFDatetimeScalarinfer_datetime_formatrc dSNrD rirrTrrryrrrrrzs rF to_datetimern CrESeries | DictConvertiblec dSrrDrs rFrrrrE list | tuple | Index | ArrayLiker3c dSrrDrs rFrrrrEunix2DatetimeScalarOrArrayConvertible | DictConvertiblebool | lib.NoDefaultlib.NoDefault | boolr8DatetimeIndex | Series | DatetimeScalar | NaTType | Nonec R|tjur|dvrtd|tjur"tjdt |dkr(tjdt t |dS| dkrt|| |}tt|||||| } t|tr9|} |r3|j | d } n:|d } n#t|tret!||| | } | js|| } n| |j|}|||j|j } nt|t.t0jfrt5|||} nut|t6rGt!||| | } | jst9|| |j } n.| |||j } nt;|r t=t>t@tBtDtFj$d t6f|}t!||| | } n/#tJ$r"|dkrddl&m'}|gtP} YnwxYw| jst9|| } np| ||} nc| tGj)|g|d} t|tTr)t| tFj+rtU| } | S)a7: 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 : {'ignore', '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`. - If :const:`'ignore'`, then invalid parsing will return the input. 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. .. warning:: In a future version of pandas, parsing datetimes with mixed time zones will raise an error unless `utc=True`. Please specify `utc=True` to opt in to the new behaviour and silence this warning. To create a `Series` with mixed offsets and `object` dtype, please use `apply` and `datetime.datetime.strptime`. 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. infer_datetime_format : bool, default False If :const:`True` and no `format` is given, attempt to infer the format of the datetime strings based on the first non-NaN element, and if it can be inferred, switch to a faster method of parsing them. In some cases this can increase the parsing speed by ~5-10x. .. deprecated:: 2.0.0 A strict version of this argument is now the default, passing it has no effect. 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``. 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[ns] 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[ns]', 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('13000101', 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[ns]', 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[ns, 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 show a warning unless `utc=True`. If you specify `utc=False` the warning below will be shown and a simple :class:`Index` containing :class:`datetime.datetime` objects will be returned: >>> pd.to_datetime(['2020-10-25 02:00 +0200', ... '2020-10-25 04:00 +0100']) # doctest: +SKIP FutureWarning: In a future version of pandas, parsing datetimes with mixed time zones will raise an error unless `utc=True`. Please specify `utc=True` to opt in to the new behaviour and silence this warning. To create a `Series` with mixed offsets and `object` dtype, please use `apply` and `datetime.datetime.strptime`. Index([2020-10-25 02:00:00+02:00, 2020-10-25 04:00:00+01:00], dtype='object') - A mix of timezone-aware and timezone-naive inputs is also converted to a simple :class:`Index` containing :class:`datetime.datetime` objects: >>> from datetime import datetime >>> pd.to_datetime(["2020-01-01 01:00:00-01:00", ... datetime(2020, 1, 1, 3, 0)]) # doctest: +SKIP FutureWarning: In a future version of pandas, parsing datetimes with mixed time zones will raise an error unless `utc=True`. Please specify `utc=True` to opt in to the new behaviour and silence this warning. To create a `Series` with mixed offsets and `object` dtype, please use `apply` and `datetime.datetime.strptime`. Index([2020-01-01 01:00:00-01:00, 2020-01-01 03:00:00], dtype='object') | 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[ns, 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[ns, 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[ns, UTC]', freq=None) >rISO8601z8Cannot use 'exact' when 'format' is 'mixed' or 'ISO8601'zThe argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.r\rzerrors='ignore' is deprecated and will raise in a future version. Use to_datetime without passing `errors` and catch exceptions explicitly insteadNr)rrrTrrrr)rrrr8rrr}r~),r no_defaultrrarbr FutureWarningrrrrrrrrr'remptyrr _constructorrrr&rMutableMapping_assemble_from_unit_mappingsr2rr"r r rrr-rrrrr8rrrobool_)rirrTrrryrrrrrzr{rrvaluesargcr8s rFrrs}n  CN""v1E'E'ESTTTCN22  3 ())       ! '))      {t VT22#  #y!!0"  0v!..// C # #)""37GHH   NWW[))FF%%ck6::F%%fCICH%MMFF C,(:; < <""-c63?? C   ""37GHH   B+C38LLLFF%%c6AAAFF c  " 3 dE>2:xNOQTD'tVU>FF%%dF33FF!!"(C5//6::1= c4  "Z%A%A "&\\F MsAI00)JJr<yearsr=monthsr>daysrJhrKrLmrMrNsrOrP millisecond millisecondsrQ microsecondrR) microsecondsrR nanosecond nanosecondsc ddlm}mm}||}|jjst ddfd|D}d|D}gd}tt|t|z }t|r(d |} t d | d tt|ttz } t| r(d | } t d | d fd } | ||ddz| ||ddzz| ||dz} t| d|} n,#t t f$r}t d||d}~wwxYwgd}|D]n}||}|U||vrQ | || |||z } ?#t t f$r}t d|d||d}~wwxYwo| S)a. assemble the unit specified fields from the arg (DataFrame) Return a Series for actual parsing Parameters ---------- arg : DataFrame errors : {'ignore', '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` - If :const:`'ignore'`, then invalid parsing will return the input utc : bool Whether to convert/localize timestamps to UTC. Returns ------- Series r)r7 to_numeric to_timedeltaz#cannot assemble with duplicate keysc|tvr t|S|tvrt|S|Sr) _unit_maplower)values rFrz'_assemble_from_unit_mappings..fsE I  U# # ;;==I % %U[[]]+ + rEc(i|]}||SrDrD).0krs rF z0_assemble_from_unit_mappings..s# ( ( (Aqqtt ( ( (rEci|]\}}|| SrDrD)rr vs rFr!z0_assemble_from_unit_mappings..s...A1...rE)r<r=r>,zNto assemble mappings requires at least that [year, month, day] be specified: [z ] is missingz9extra keys have been passed to the datetime assemblage: [rcx|}t|jr|dd}|S)Nrint64Fr)r!rr)r rrs rFrz,_assemble_from_unit_mappings..coercesEF6222 FL ) ) 8]]7]77F rEr<i'r=dr>z%Y%m%d)ryrrzcannot assemble the datetimes: N)rrrrPrQrR)rrzcannot assemble the datetimes [z]: )rr7rrcolumnsrrkeysitemssortedrtrrjoinrr rruget)rirrr7rrunit_revrequiredreq _requiredexcess_excessrr runitsurrrs ` @@rFrrqs@( )C..C ; @>??? ) ( ( (SXXZZ ( ( (D.....H(''H XX]]__!5!55 6 6C 3xx HHSMM  I1: I I I   C ((3y/?/?/A/A+B+BB C CF 6{{ ((6"" R R R R    s8F#$%%- &Xg&' ( (3 . / &Xe_% & & ' KVHVMMM z "KKK@3@@AAsJK A@@E  Q  # ,,vvc%j'9'9&QQQQz*    EeEEEE  Ms0G""H 3HH 2 II?$I::I?)rrxr)F)rTrUrVrW)rhN)rirjrkrlrmrnrVro) rirjryrWrzror{r rVr8)FN)rrrrorrrVr2r)rirrr8rrrVr2)NFNrNNT)ryrWrrrrorrWrrrTrUrrUrro) rrorr`rrorr`rVr2)rrorr`rVr2) ..........)rirrrrTrorrorroryrWrrorrWrrorzrorVr)rirrrrTrorrorroryrWrrorrWrrorzrorVr8)rirrrrTrorrorroryrWrrorrWrrorzrorVr3)rirrrrTrorrorroryrWrrrrWrrrr`rzrorVr)rrrro)r __future__r collectionsrdatetimer functoolsr itertoolsrtypingrr r r r r ranumpyr pandas._libsrrpandas._libs.tslibsrrrrrrrpandas._libs.tslibs.conversionrpandas._libs.tslibs.parsingrrpandas._libs.tslibs.strptimerpandas._typingrrrpandas.util._exceptionsrpandas.core.dtypes.commonrrr r!r"r#pandas.core.dtypes.dtypesr$r%pandas.core.dtypes.genericr&r' pandas.arraysr(r)r*pandas.core.algorithmsr+pandas.core.arraysr,pandas.core.arrays.baser-pandas.core.arrays.datetimesr.r/r0pandas.core.constructionr1pandas.core.indexes.baser2pandas.core.indexes.datetimesr3collections.abcr4pandas._libs.tslibs.nattyper5pandas._libs.tslibs.timedeltasr6rr7r8rrrjrlr`Scalar datetime64rrr;r:rIDictConvertiblersrgrxrrrrrrrrrrr__all__rDrErFrVs""""""EDDDDD877777 544444  *)))))222222222222 322222******777777 ((((((333333::::::ul23 ucz vtR]23#(9I)I#J V eFCK&8,FGy     'u    (+56 0QU99999x////fEI<<<<<@!CCCCC:!#* !K9K9K9K9K9\88884AAAAHEEEP $'"%         $'"%         $'"%       $$+"%.25.sssssn   F  V  W  g    5    E   C  S  c s  c s  $ 4 D   $! "4# $ +    2[[[[|   rE