Ë
|
nñúhÆ ã ó d dl mZ d dlmZ d dlZd dlmZmZ d dlZ d dl
|
m Z m Z d dl mZmZmZmZmZmZmZmZmZ d dlmZ d dlmZmZ d d l m Z m Z m Z m Z m!Z! d d
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l"m#Z$ d d l%m&Z& d d l'm(Z(m)Z)m*Z*m+Z+m,Z,m-Z-m.Z. d d l/m0Z0 d dl1m2Z2 d dl3m4Z4m5Z5 d dl6m7Z7 d dl8m9Z: d dl;m<Z< d dl=m>c m?Z@ d dlAmBZB er d dlCmDZD d dlEmFZFmGZGmHZHmIZImJZJmKZK d dlLmMZM d dlNZNd dZO G d de:j « ZQ d d dZRd!d"dZSd#d$d ZTd%d ZUy)&é )Ú annotations)Ú timedeltaN)Ú TYPE_CHECKINGÚcast)ÚlibÚtslibs) ÚNaTÚNaTTypeÚTickÚ TimedeltaÚastype_overflowsafeÚget_supported_dtypeÚiNaTÚis_supported_dtypeÚperiods_per_second)Úcast_from_unit_vectorized)Úget_timedelta_daysÚget_timedelta_field)Úarray_to_timedelta64Úfloordiv_object_arrayÚints_to_pytimedeltaÚparse_timedelta_unitÚtruediv_object_array)Úfunction)Úvalidate_endpoints)Ú TD64NS_DTYPEÚis_float_dtypeÚis_integer_dtypeÚis_object_dtypeÚ is_scalarÚis_string_dtypeÚ pandas_dtype)ÚExtensionDtype)Úisna)ÚnanopsÚ roperator)Údatetimelike_accumulations)Ú datetimelike)Úgenerate_regular_range)Úunpack_zerodim_and_defer)ÚIterator)ÚAxisIntÚDateTimeErrorChoicesÚDtypeObjÚNpDtypeÚSelfÚnpt©Ú DataFramec óJ dfd }| |_ d| d|_ t |« S )Nc óÊ | j }dk( rt || j ¬« }nt || j ¬« }| j r| j |d d¬« }|S )NÚdays©ÚresoÚfloat64)Ú
|
fill_valueÚconvert)Úasi8r Ú_cresor Ú_hasnaÚ_maybe_mask_results)ÚselfÚvaluesÚresultÚaliass úPH:\Change_password\venv_build\Lib\site-packages\pandas/core/arrays/timedeltas.pyÚfz_field_accessor.<locals>.fR sa ø ØØ F?Ü'¨°T·[±[ÔAFô
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)¨°¸T¿[¹[ÔIFØ ;;Ø×-Ñ-Ø 4°ð .ó Fð ó ú
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)Úreturnz
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np.ndarray)Ú__name__Ú__doc__Úproperty)ÚnamerC Ú docstringrE s ` rD Ú_field_accessorrN Q s+ ø õð AJØYKrÐ"AIÜ A;ÐrF c ó¬ e Zd ZU dZdZ ej dd« Zeej e fZ
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d Z dZ e dUd« ZdZg Zd ed
|
< g Zd ed < d gZd ed < g d¢Zd ed< eez ez dgz Zd ed< g d¢Zd ed< dVdZe dWd« ZdZeZe d « Z e def dX fd « Z e ddddYd« Z e dde jB dd dYd « Z"e dZdd d[d « Z#d\d Z$d]d!Z%d^d"Z&d_d`d$Z'dad%Z(dddddd#d&d' dbd(Z)dddd)dd#d* dcd+Z*d#d,dd fd-Z+dedfd.Z,ddd/ dgd0Z-d1 Z. e/d2« dhd3« Z0e0Z1d4 Z2d5 Z3did6Z4 e/d7« d8 « Z5 e/d9« d: « Z6 e/d;« d< « Z7 e/d=« d> « Z8 e/d?« d@ « Z9 e/dA« dB « Z: e/dC« dD « Z; e/dE« dF « Z<djdGZ=djdHZ>djdIZ?dkdJZ@dldKZA eBj dL« ZD eEdMdMeD« ZF eBj dN« ZG eEdOdOeG« ZH eBj dP« ZI eEdQdQeI« ZJ eBj dR« ZK eEdSdSeK« ZLe dmdT« ZM xZNS )nÚTimedeltaArrayal
|
Pandas ExtensionArray for timedelta data.
|
|
.. warning::
|
|
TimedeltaArray is currently experimental, and its API may change
|
without warning. In particular, :attr:`TimedeltaArray.dtype` is
|
expected to change to be an instance of an ``ExtensionDtype``
|
subclass.
|
|
Parameters
|
----------
|
values : array-like
|
The timedelta data.
|
|
dtype : numpy.dtype
|
Currently, only ``numpy.dtype("timedelta64[ns]")`` is accepted.
|
freq : Offset, optional
|
copy : bool, default False
|
Whether to copy the underlying array of data.
|
|
Attributes
|
----------
|
None
|
|
Methods
|
-------
|
None
|
|
Examples
|
--------
|
>>> pd.arrays.TimedeltaArray._from_sequence(pd.TimedeltaIndex(['1h', '2h']))
|
<TimedeltaArray>
|
['0 days 01:00:00', '0 days 02:00:00']
|
Length: 2, dtype: timedelta64[ns]
|
Útimedeltaarrayr Únsc ó. t j | d« S ©NÚm)r Ú is_np_dtype©Úxs rD ú<lambda>zTimedeltaArray.<lambda> s ¤S§_¡_°Q¸Ó%< rF )r Ú timedelta64c ó t S ©N©r ©r@ s rD Ú _scalar_typezTimedeltaArray._scalar_type s äÐrF iè z list[str]Ú
|
_other_opsÚ _bool_opsÚfreqÚ _object_ops)r6 ÚsecondsÚ microsecondsÚ nanosecondsÚ
|
_field_opsÚunitÚ_datetimelike_ops)Úto_pytimedeltaÚ total_secondsÚroundÚfloorÚceilÚas_unitÚ_datetimelike_methodsc ó |j d« }|t j k( rt S t j || j
|
¬« S )NÚi8r7 )Úviewr Ú_valuer Ú_from_value_and_resor= )r@ rX Úys rD Ú _box_funczTimedeltaArray._box_funcª s6 Ø FF4LØ
|
|
?ÜJÜ×-Ñ-¨a°d·k±kÔBÐBrF c ó. | j j S )a3
|
The dtype for the TimedeltaArray.
|
|
.. warning::
|
|
A future version of pandas will change dtype to be an instance
|
of a :class:`pandas.api.extensions.ExtensionDtype` subclass,
|
not a ``numpy.dtype``.
|
|
Returns
|
-------
|
numpy.dtype
|
)Ú_ndarrayÚdtyper^ s rD rz zTimedeltaArray.dtype° s ð" }}×"Ñ"Ð"rF Nc óz t |« }t |j « ||j k7 r t d« |S )Nz'Values resolution does not match dtype.)Ú_validate_td64_dtyperz Ú
|
ValueError)ÚclsrA rz s rD Ú_validate_dtypez TimedeltaArray._validate_dtypeÉ s7 ô % UÓ+Ü V\\Ô*Ø FLLÒ Ü Ð FÓGÐ GØ rF c ó4 t j |d« sJ t j |« rJ t |t
|
j « sJ t |« « ||j k( sJ |t |t « sJ t | - ||¬« }||_ |S )NrU )rA rz ) r rV r Ú is_unitlessÚ
|
isinstanceÚnpÚndarrayÚtyperz r ÚsuperÚ _simple_newÚ_freq)r~ rA rb rz rB Ú __class__s rD r zTimedeltaArray._simple_newÓ s ø ô u cÔ*Ð*Ð*Ü×%Ñ% eÔ,Ð,Ð,Ü&¤"§*¡*Ô-Ð;¬t°F«|Ó;Ð-Ø Ò$Ð$Ð$Ø|z¨$´Ô 5Ð5Ð5äÑ$¨F¸%Ð$Ó@Ø Ø rF F©rz Úcopyc ó |r t |« }t ||d ¬« \ }}|t ||d¬« }| j ||j |¬« S )N©r rh Fr ©rz rb )r| Úsequence_to_td64nsr r rz )r~ Údatarz r rb s rD Ú_from_sequencez TimedeltaArray._from_sequenceå sN á Ü(¨Ó/Eä'¨°4¸dÔC
|
dà Ð Ü& t°5¸uÔEDàt¨4¯:©:¸DÓAÐArF )rz r rb rh c óÎ |r t |« }|dvsJ t |||¬« \ }}|t ||d¬« }| j ||j |¬« }|j |i « |S )zo
|
_from_sequence_not_strict but without responsibility for finding the
|
result's `freq`.
|
©ÚYrv ÚMr Fr r )r| r r r rz Ú_maybe_pin_freq)r~ r rz r rb rh Ú inferred_freqrB s rD Ú_from_sequence_not_strictz(TimedeltaArray._from_sequence_not_strictñ ss ñ Ü(¨Ó/Eà?Ñ*Ð*Ð*ä 0°¸DÀtÔ LÑmà Ð Ü& t°5¸uÔEDà ¨T¯Z©Z¸m ÓLà× Ñ t RÔ(Ø rF ©rh c óæ t j |« }| t d |||fD « « r t d« t j
|
||||« dk7 r t d« |t |« j d« }|t |« j d« }||dvr t d« d}|||j |d¬ « }|||j |d¬ « }t |« \ }}|t |||||¬
|
« } n:t j |j |j |« j d « } |s| d d } |s| d d } | j d| d« }
|
| j |
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|
j |¬« S )Nc 3 ó$ K | ] }|d u
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y wr\ © )Ú.0rX s rD ú <genexpr>z1TimedeltaArray._generate_range.<locals>.<genexpr> s è ø Ò I¨a T¤ Ñ Iùs z1Must provide freq argument if no data is suppliedé zVOf the four parameters: start, end, periods, and freq, exactly three must be specifiedrR )ÚsÚmsÚusrR z+'unit' must be one of 's', 'ms', 'us', 'ns'F)Úround_okr rr é éÿÿÿÿzm8[ú]r )ÚdtlÚvalidate_periodsÚanyr} ÚcomÚcount_not_noner ro r r) r Úlinspacert Úastypers r rz ) r~ ÚstartÚendÚperiodsrb Úclosedrh Ú left_closedÚ right_closedÚindexÚ
|
td64valuess rD Ú_generate_rangez TimedeltaArray._generate_range s ô ×&Ñ& wÓ/Ø <CÑ I°G¸UÀCÐ3HÔ IÔ IÜ Ð PÓQÐ Qä × Ñ e S¨'°4Ó 8¸AÒ =Ü ð<óð ð
|
Ð Ü eÓ$×,Ñ,¨TÓ2Eà ?ÜC.×(Ñ(¨Ó.Cà Ð ØÐ2Ñ2Ü Ð!NÓOÐOàDà Ð Ð!1ØMM $°MÓ7EØ ?tÐ /Ø++d¨U+Ó3Cä$6°vÓ$>Ñ! \à Ð Ü*¨5°#°wÀÈ4ÔPEäKK § ¡ ¨c¯j©j¸'ÓB×IÑIÈ$ÓOEáØ!"IEÙØ#2JEàZZ # d V¨1 Ó.
|
Øz°×1AÑ1AÈÓMÐMrF c ó$ t || j « s|t ur t d« | j |« |t u r*t j |j | j « S |j | j « j S )Nz 'value' should be a Timedelta.) r r_ r r} Ú_check_compatible_withr rZ rt rh ro Úasm8©r@ Úvalues rD Ú _unbox_scalarz TimedeltaArray._unbox_scalar? sl Ü% ×!2Ñ!2Ô3¸ÄSÑ8HÜ Ð =Ó>Ð >Ø ×#Ñ# EÔ*Ø C<Ü>> %§,¡,°· ± Ó:Ð :à== §¡Ó+×0Ñ0Ð 0rF c ó t |« S r\ r] rº s rD Ú_scalar_from_stringz"TimedeltaArray._scalar_from_stringH s ÜÓ Ð rF c ó y r\ r ©r@ Úothers rD r¸ z%TimedeltaArray._check_compatible_withK s à rF Tc ó® t |« }t j |d« r|| j k( r|r| j « S | S t |« rIt | j |d¬« }t | « j ||j | j ¬« S t d| j d| d« t j j | ||¬« S )NrU F©r r zCannot convert from z to z1. Supported resolutions are 's', 'ms', 'us', 'ns')r" r rV rz r r r ry r
r rb r} r§ ÚDatetimeLikeArrayMixinr )r@ rz r Ú
|
res_valuess rD r zTimedeltaArray.astypeR sÐ ô
|
UÓ#ä ??5 #Ô &Ø
|
|
Ò"ÙØ 99;Ð&Ø ä! %Ô(ä 0°· ± ÀÈEÔ R
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ÜDz×-Ñ-Ø j×&6Ñ&6¸T¿Y¹Yð .ó ð ô !Ø*¨4¯:©:¨,°d¸5¸'ð BFð Fóð ô
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×)Ñ)×0Ñ0°°uÀ4Ð0ÓHÐHrF c # ó4 K | j dkD r!t t | « « D ] }| | y | j }t | « }d}||z dz }t |« D ]3 }||z }t |dz |z |« }t ||| d¬« }|E d { 5 y 7 w)Nr¤ i' T©Úbox)ÚndimÚrangeÚlenry Úminr ) r@ Úir ÚlengthÚ chunksizeÚchunksÚstart_iÚend_iÚ converteds rD Ú__iter__zTimedeltaArray.__iter__m s¬ è ø Ø 99q=Ü3t9Ó%ò Ø1g ñ ð ==DÜYFØ IØ Ñ)¨QÑ.FÜ6]ò %Øi-ÜQ U iÑ /°Ó8Ü /°°W¸UÐ0CÈÔ N Ø$×$Ñ$ñ %ð %ús B BÂBÂBr )Úaxisrz ÚoutÚkeepdimsÚinitialÚskipnaÚ min_countc ó¢ t j d||||d« t j | j |||¬« }| j ||« S )Nr )rz rÖ r× rØ )rÕ rÙ rÚ )ÚnvÚ validate_sumr% Únansumry Ú_wrap_reduction_result) r@ rÕ rz rÖ r× rØ rÙ rÚ rB s rD ÚsumzTimedeltaArray.sum sP ô Ø %¨¸ÈgÑVô
|
ô Ø MM ¨V¸yô
|
ð ×*Ñ*¨4°Ó8Ð8rF r¤ )rÕ rz rÖ Úddofr× rÙ c óæ t j d|||dd¬« t j | j |||¬« }|| j
|
dk( r| j |« S | j |« S )Nr )rz rÖ r× Ústd)Úfname)rÕ rÙ rá r¤ )rÜ Úvalidate_stat_ddof_funcr% Únanstdry rÉ rw Ú_from_backing_data)r@ rÕ rz rÖ rá r× rÙ rB s rD rã zTimedeltaArray.std si ô ×"Ñ"Ø %¨¸ÑBÈ%õ
|
ô t}}°4ÀÈTÔRØ <499¨>Ø>> &Ó)Ð )Ø×&Ñ& vÓ.Ð.rF )rÙ c ó |dk( rZt t |« } || j j « fd|i|¤}t | « j |d | j ¬« S |dk( r t d« t | $ |fd|i|¤S )NÚcumsumrÙ )rb rz Úcumprodz$cumprod not supported for Timedelta.)
|
Úgetattrr' ry r r
r rz Ú TypeErrorr Ú _accumulate)r@ rL rÙ ÚkwargsÚoprB r s rD rí zTimedeltaArray._accumulateª s ø Ø 8Ò ÜÔ3°TÓ:BÙ ×*Ñ*Ó,ÑF°VÐF¸vÑFFä:×)Ñ)¨&°tÀ4Ç:Á:Ð)ÓNÐ NØ YÒ ÜÐ BÓCÐ Cô 7Ñ& tÑE°FÐE¸fÑEÐ ErF c ó" ddl m} || d¬« S )Nr ©Úget_format_timedelta64TrÇ )Úpandas.io.formats.formatrò )r@ Úboxedrò s rD Ú
|
_formatterzTimedeltaArray._formatter¹ s ÝCá% d°Ô5Ð5rF )Úna_repÚ date_formatc ón ddl m} || |« } t j |dd« | j « S )Nr rñ r¤ )ró rò r Ú
|
frompyfuncry )r@ rö r÷ rî rò Ú formatters rD Ú_format_native_typesz#TimedeltaArray._format_native_types¾ s6 õ Dñ +¨4°Ó8 ð .r}}Y¨¨1Ó-¨d¯m©mÓ<Ð<rF c ó t |t « rJ t dt |« j dt | « j « )Nzcannot add the type z to a )r r rì r
rI rÀ s rD Ú _add_offsetzTimedeltaArray._add_offsetÌ sE Ü e¤TÔ*Ð*Ð*ÜØ"¤4¨£;×#7Ñ#7Ð"8¸¼tÀD»z×?RÑ?RÐ>SÐ Tó
|
ð
|
rF Ú__mul__c ó$ t |« r©| j |z }|j j dk7 r!t dt |« j « d }| j +t |« s | j |z }|j dk( rd }t | « j ||j |¬« S t |d« st j |« }t |« t | « k7 r+t j |j d« s t# d« t% |j « rq| j }t' t | « « D cg c] }|| || z }}t j |« }t | « j ||j ¬« S | j |z }|j j dk7 r!t dt |« j « t | « j ||j ¬« S c c}w )NrU zCannot multiply with r r rz z$Cannot multiply with unequal lengths©rz )r ry rz Úkindrì r
rI rb r$ Únr Úhasattrr ÚarrayrË r rV r} r rÊ )r@ rÁ rB rb Úarrr s rD rþ zTimedeltaArray.__mul__Ò sµ ä UÔ à]] UÑ*FØ||× Ñ CÒ'ô Ð"7¼¸U» ×8LÑ8LÐ7MÐ NÓOÐOØDØyyÐ$¬T°%¬[Øyy 5Ñ(Ø66Q;à DÜ:×)Ñ)¨&¸¿ ¹ È4Ð)ÓPÐ PäugÔ&äHHUOEÜ u:TÒ "¬3¯?©?¸5¿;¹;ÈÔ+Lô Ð CÓDÐ Dä 5;;Ô 'ð --CÜ16´s¸4³yÓ1AÖB¨Ac!fu QxÓ'ÐBFÐBÜXXfÓ%FÜ:×)Ñ)¨&¸¿ ¹ Ð)ÓEÐ Eð Ñ&Ø <<× Ñ Ò #ô Ð 3´D¸³K×4HÑ4HÐ3IÐ JÓKÐ KÜDz×%Ñ% f°F·L±LÐ%ÓAÐAùò Cs ÅH c óâ t || j « rt |« }t d|« t u rPt j | j t
|
j ¬« }|j t
|
j « |S || j |« S |t j t j fv r7t dt! |« j" dt! | « j" « || j |« }d}| j$ 9| j$ |z }|j& dk( r| j$ j& dk7 rd}t! | « j) ||j* |¬« S )zv
|
Shared logic for __truediv__, __rtruediv__, __floordiv__, __rfloordiv__
|
with scalar 'other'.
|
úTimedelta | NaTTyper zCannot divide z by Nr r )r Ú_recognized_scalarsr r r r ÚemptyÚshaper9 ÚfillÚnanry r& ÚrtruedivÚ rfloordivrì r
rI rb Únanosr rz )r@ rÁ rï ÚresrB rb s rD Ú_scalar_divlike_opz!TimedeltaArray._scalar_divlike_opþ s0 ô
|
eT× 5Ñ 5Ô 6Ü eÓ$Eô Ð)¨5Ó1´SÑ8ähhtzz´·±Ô<ØÔ Ø
|
ñ dmm UÓ+Ð +ð i×(Ñ(¬)×*=Ñ*=Ð>Ñ>Ü Ø$¤T¨%£[×%9Ñ%9Ð$:¸$¼tÀD»z×?RÑ?RÐ>SÐTóð ñ uÓ-FØDàyyÐ$ð yy 5Ñ(Ø:: ? t§y¡y§¡¸!Ò';ð Dä:×)Ñ)¨&¸¿ ¹ È4Ð)ÓPÐ PrF c ó t |d« st j |« }t |« t | « k7 r t d« |S )Nrz z*Cannot divide vectors with unequal lengths)r r r rË r} rÀ s rD Ú_cast_divlike_opz TimedeltaArray._cast_divlike_op' s: ÜugÔ&äHHUOEä u:TÒ "Ü Ð IÓJÐ JØ rF c óZ || j t j |« « }t |j « st |j « rH|t j t j fv r&t | « j ||j ¬« S |t j t j fv rp| j « t |« z }|j « rD|j t j « }t j" ||t j$ « |S )z
|
Shared logic for __truediv__, __floordiv__, and their reversed versions
|
with timedelta64-dtype ndarray other.
|
r )ry r Úasarrayr rz r ÚoperatorÚtruedivÚfloordivr
r r& r r$ r© r r9 Úputmaskr )r@ rÁ rï rB Úmasks rD Ú_vector_divlike_opz!TimedeltaArray._vector_divlike_op0 sÕ ñ DMM¤2§:¡:¨eÓ#4Ó5ä U[[Ô )¬^¸E¿K¹KÔ-HÈbÜ × Ñ Ü × Ñ ðU
|
ñ O
|
ô :×)Ñ)¨&¸¿ ¹ Ð)ÓEÐ Eà (×#Ñ#¤Y×%8Ñ%8Ð9Ñ 9Ø99;¤ e£Ñ,DØxxzØ ¤r§z¡zÓ2Ü
|
|
6 4¬¯©Ô0à rF Ú __truediv__c ó¬ t j }t |« r| j ||« S | j |« }t j |j d« s*t |j « st |j « r| j ||« S t |j « rt j |« }| j dkD rYt | |« D cg c]
|
\ }}||z }}}|D cg c] }|j! dd« }}t j" |d¬« }|S t% | j& |« }|S t( S c c}}w c c}w ©NrU r¤ r¥ r )rÕ )r r r r r r rV rz r r r r r r rÉ ÚzipÚreshapeÚ concatenater ry ÚNotImplemented© r@ rÁ rï ÚleftÚrightÚres_colsrX Ú res_cols2rB s rD r zTimedeltaArray.__truediv__F s ô × Ñ Ü UÔ Ø×*Ñ*¨5°"Ó5Ð 5à×%Ñ% eÓ,ä OOEKK¨Ô -Ü § ¡ Ô,Ü ekkÔ*à×*Ñ*¨5°"Ó5Ð 5ä 5;;Ô 'ÜJJuÓ%EØyy1}Ü<?ÀÀeÓ<L×M©[¨T°5D 5LÐMÑMØ7?Ö @°!QYY q¨"Õ -Ð @ Ð @Ü ¨ ¸Ô:ð Mô .¨d¯m©m¸UÓCàMô "Ð !ùó NùÚ @s Ã#E Ã9EÚ __rtruediv__c ó t j }t |« r| j ||« S | j |« }t j |j d« r| j ||« S t |j « r?t t | « « D cg c] }|| | | z }}t j |« S t S c c}w rT )r& r r r r r rV rz r r rÊ rË r r r" )r@ rÁ rï r Ú result_lists rD r( zTimedeltaArray.__rtruediv__c s³ ô × Ñ Ü UÔ Ø×*Ñ*¨5°"Ó5Ð 5à×%Ñ% eÓ,Ü ??5;;¨Ô ,Ø×*Ñ*¨5°"Ó5Ð 5ä U[[Ô )ô 8=¼SÀ»YÓ7GÖH°!5 8 d¨1¡gÓ-ÐHKÐHÜ88KÓ(Ð (ô "Ð !ùò Is  C Ú __floordiv__c óÔ t j }t |« r| j ||« S | j |« }t j |j d« s*t |j « st |j « r| j ||« S t |j « r©t j |« }| j dkD rXt | |« D cg c]
|
\ }}||z }}}|D cg c] }|j! dd« }}t j" |d¬« }nt% | j& |« }|j t( k( sJ |S t* S c c}}w c c}w r )r r r r r r rV rz r r r r r r rÉ r r r! r ry Úobjectr" r# s rD r+ zTimedeltaArray.__floordiv__x s" ä × Ñ Ü UÔ Ø×*Ñ*¨5°"Ó5Ð 5à×%Ñ% eÓ,ä OOEKK¨Ô -Ü § ¡ Ô,Ü ekkÔ*à×*Ñ*¨5°"Ó5Ð 5ä U[[Ô )ÜJJuÓ%EØyy1}Ü=@ÀÀuÓ=M×N©k¨d°ED EMÐNÑNØ7?Ö @°!QYY q¨"Õ -Ð @ Ð @Ü ¨ ¸Ô:ä.¨t¯}©}¸eÓDà<<¤6Ò)Ð )Ð)ØMô "Ð !ùó OùÚ @s Ã#E Ã9E%Ú __rfloordiv__c ó¤ t j }t |« r| j ||« S | j |« }t j |j d« r| j ||« S t |j « rAt t | « « D cg c] }|| | | z }}t j |« }|S t S c c}w rT )r& r r r r r rV rz r r rÊ rË r r r" )r@ rÁ rï r r* rB s rD r. z TimedeltaArray.__rfloordiv__ s³ ä × Ñ Ü UÔ Ø×*Ñ*¨5°"Ó5Ð 5à×%Ñ% eÓ,Ü ??5;;¨Ô ,Ø×*Ñ*¨5°"Ó5Ð 5ä U[[Ô )Ü8=¼cÀ$»iÓ8HÖI°15 8 t¨A¡wÓ.ÐIKÐIÜXXkÓ*FØMô "Ð !ùò Js  C Ú__mod__c óZ t || j « r t |« }| | |z |z z
|
S r\ ©r r r rÀ s rD r0 zTimedeltaArray.__mod__§ s2 ô eT× 5Ñ 5Ô 6Ü eÓ$EØtu}¨Ñ-Ñ-Ð-rF Ú__rmod__c óZ t || j « r t |« }||| z | z z
|
S r\ r2 rÀ s rD r3 zTimedeltaArray.__rmod__® s2 ô eT× 5Ñ 5Ô 6Ü eÓ$EØ ¨Ñ-Ñ-Ð-rF Ú
|
__divmod__c óf t || j « r t |« }| |z }| ||z z
|
}||fS r\ r2 ©r@ rÁ Úres1Úres2s rD r5 zTimedeltaArray.__divmod__µ s? ô eT× 5Ñ 5Ô 6Ü eÓ$Eàu}ØdUlÑ"ØTzÐrF Ú __rdivmod__c óf t || j « r t |« }|| z }||| z z
|
}||fS r\ r2 r7 s rD r: zTimedeltaArray.__rdivmod__¿ s? ô eT× 5Ñ 5Ô 6Ü eÓ$Eà}Øtd{Ñ"ØTzÐrF c ó d }| j | j }t | « j | j | j |¬« S ©Nr )rb r
r ry rz )r@ rb s rD Ú__neg__zTimedeltaArray.__neg__É sB ØØ 99Ð ØII:DÜDz×%Ñ% t§}¡} n¸D¿J¹JÈTÐ%ÓRÐRrF c ó t | « j | j j « | j | j
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¬« S r= )r
r ry r rz rb r^ s rD Ú__pos__zTimedeltaArray.__pos__Ï s: ÜDz×%Ñ%Ø MM× Ñ Ó ¨¯
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©
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¸¿¹ð &ó
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ð
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rF c ó t | « j t j | j « | j
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¬« S )Nr )r
r r Úabsry rz r^ s rD Ú__abs__zTimedeltaArray.__abs__Ô s- äDz×%Ñ%¤b§f¡f¨T¯]©]Ó&;À4Ç:Á:Ð%ÓNÐNrF c ól t | j « }| j | j |z d¬« S )a{
|
Return total duration of each element expressed in seconds.
|
|
This method is available directly on TimedeltaArray, TimedeltaIndex
|
and on Series containing timedelta values under the ``.dt`` namespace.
|
|
Returns
|
-------
|
ndarray, Index or Series
|
When the calling object is a TimedeltaArray, the return type
|
is ndarray. When the calling object is a TimedeltaIndex,
|
the return type is an Index with a float64 dtype. When the calling object
|
is a Series, the return type is Series of type `float64` whose
|
index is the same as the original.
|
|
See Also
|
--------
|
datetime.timedelta.total_seconds : Standard library version
|
of this method.
|
TimedeltaIndex.components : Return a DataFrame with components of
|
each Timedelta.
|
|
Examples
|
--------
|
**Series**
|
|
>>> s = pd.Series(pd.to_timedelta(np.arange(5), unit='d'))
|
>>> s
|
0 0 days
|
1 1 days
|
2 2 days
|
3 3 days
|
4 4 days
|
dtype: timedelta64[ns]
|
|
>>> s.dt.total_seconds()
|
0 0.0
|
1 86400.0
|
2 172800.0
|
3 259200.0
|
4 345600.0
|
dtype: float64
|
|
**TimedeltaIndex**
|
|
>>> idx = pd.to_timedelta(np.arange(5), unit='d')
|
>>> idx
|
TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
|
dtype='timedelta64[ns]', freq=None)
|
|
>>> idx.total_seconds()
|
Index([0.0, 86400.0, 172800.0, 259200.0, 345600.0], dtype='float64')
|
N)r: )r r= r? r< )r@ Úppss rD rk z TimedeltaArray.total_secondsÛ s1 ôl ! §¡Ó-Ø×'Ñ'¨¯ © °C©ÀDÐ'ÓIÐIrF c ó, t | j « S )a
|
Return an ndarray of datetime.timedelta objects.
|
|
Returns
|
-------
|
numpy.ndarray
|
|
Examples
|
--------
|
>>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='D')
|
>>> tdelta_idx
|
TimedeltaIndex(['1 days', '2 days', '3 days'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.to_pytimedelta()
|
array([datetime.timedelta(days=1), datetime.timedelta(days=2),
|
datetime.timedelta(days=3)], dtype=object)
|
)r ry r^ s rD rj z TimedeltaArray.to_pytimedelta s ô$ # 4§=¡=Ó1Ð1rF aC Number of days for each element.
|
|
Examples
|
--------
|
For Series:
|
|
>>> ser = pd.Series(pd.to_timedelta([1, 2, 3], unit='d'))
|
>>> ser
|
0 1 days
|
1 2 days
|
2 3 days
|
dtype: timedelta64[ns]
|
>>> ser.dt.days
|
0 1
|
1 2
|
2 3
|
dtype: int64
|
|
For TimedeltaIndex:
|
|
>>> tdelta_idx = pd.to_timedelta(["0 days", "10 days", "20 days"])
|
>>> tdelta_idx
|
TimedeltaIndex(['0 days', '10 days', '20 days'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.days
|
Index([0, 10, 20], dtype='int64')r6 a Number of seconds (>= 0 and less than 1 day) for each element.
|
|
Examples
|
--------
|
For Series:
|
|
>>> ser = pd.Series(pd.to_timedelta([1, 2, 3], unit='s'))
|
>>> ser
|
0 0 days 00:00:01
|
1 0 days 00:00:02
|
2 0 days 00:00:03
|
dtype: timedelta64[ns]
|
>>> ser.dt.seconds
|
0 1
|
1 2
|
2 3
|
dtype: int32
|
|
For TimedeltaIndex:
|
|
>>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='s')
|
>>> tdelta_idx
|
TimedeltaIndex(['0 days 00:00:01', '0 days 00:00:02', '0 days 00:00:03'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.seconds
|
Index([1, 2, 3], dtype='int32')rd aÝ Number of microseconds (>= 0 and less than 1 second) for each element.
|
|
Examples
|
--------
|
For Series:
|
|
>>> ser = pd.Series(pd.to_timedelta([1, 2, 3], unit='us'))
|
>>> ser
|
0 0 days 00:00:00.000001
|
1 0 days 00:00:00.000002
|
2 0 days 00:00:00.000003
|
dtype: timedelta64[ns]
|
>>> ser.dt.microseconds
|
0 1
|
1 2
|
2 3
|
dtype: int32
|
|
For TimedeltaIndex:
|
|
>>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='us')
|
>>> tdelta_idx
|
TimedeltaIndex(['0 days 00:00:00.000001', '0 days 00:00:00.000002',
|
'0 days 00:00:00.000003'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.microseconds
|
Index([1, 2, 3], dtype='int32')re añ Number of nanoseconds (>= 0 and less than 1 microsecond) for each element.
|
|
Examples
|
--------
|
For Series:
|
|
>>> ser = pd.Series(pd.to_timedelta([1, 2, 3], unit='ns'))
|
>>> ser
|
0 0 days 00:00:00.000000001
|
1 0 days 00:00:00.000000002
|
2 0 days 00:00:00.000000003
|
dtype: timedelta64[ns]
|
>>> ser.dt.nanoseconds
|
0 1
|
1 2
|
2 3
|
dtype: int32
|
|
For TimedeltaIndex:
|
|
>>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='ns')
|
>>> tdelta_idx
|
TimedeltaIndex(['0 days 00:00:00.000000001', '0 days 00:00:00.000000002',
|
'0 days 00:00:00.000000003'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.nanoseconds
|
Index([1, 2, 3], dtype='int32')rf c ó¶ ddl m} g d¢| j }|rfd}nd } || D cg c]
|
} ||« c}¬« }|s|j d« }|S c c}w )aØ
|
Return a DataFrame of the individual resolution components of the Timedeltas.
|
|
The components (days, hours, minutes seconds, milliseconds, microseconds,
|
nanoseconds) are returned as columns in a DataFrame.
|
|
Returns
|
-------
|
DataFrame
|
|
Examples
|
--------
|
>>> tdelta_idx = pd.to_timedelta(['1 day 3 min 2 us 42 ns'])
|
>>> tdelta_idx
|
TimedeltaIndex(['1 days 00:03:00.000002042'],
|
dtype='timedelta64[ns]', freq=None)
|
>>> tdelta_idx.components
|
days hours minutes seconds milliseconds microseconds nanoseconds
|
0 1 0 3 0 0 2 42
|
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k( sJ | j dk7 sJ | |fS )aÖ
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Parameters
|
----------
|
data : list-like
|
copy : bool, default False
|
unit : str, optional
|
The timedelta unit to treat integers as multiples of. For numeric
|
data this defaults to ``'ns'``.
|
Must be un-specified if the data contains a str and ``errors=="raise"``.
|
errors : {"raise", "coerce", "ignore"}, default "raise"
|
How to handle elements that cannot be converted to timedelta64[ns].
|
See ``pandas.to_timedelta`` for details.
|
|
Returns
|
-------
|
converted : numpy.ndarray
|
The sequence converted to a numpy array with dtype ``timedelta64[ns]``.
|
inferred_freq : Tick or None
|
The inferred frequency of the sequence.
|
|
Raises
|
------
|
ValueError : Data cannot be converted to timedelta64[ns].
|
|
Notes
|
-----
|
Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause
|
errors to be ignored; they are caught and subsequently ignored at a
|
higher level.
|
r NrP )Úcls_name©rh ÚerrorsFr rR zm8[ns]rU r zdtype z' cannot be converted to timedelta64[ns]rà Úm8) r r§ Ú!ensure_arraylike_for_datetimeliker rP rb rz r- r! Ú_objects_to_td64nsr Ú_ints_to_td64nsr r# Ú_maskÚ_datar Úisnanr r rs r rV r r r rì r r r )r r rh rq r Ú copy_mader Ú new_dtypes rD r r æ s ðH Ñ &Ð&Ð &àMØ ÐÜ# DÓ)ä×6Ñ6Ø dÐ -ôJD$ô $Ô'Ø ð zzVÒ¨t¯z©zÔ :ä! $¨T¸&ÔAØä $**Ô %ä)¨$°TÔ:iØÒ%I ä
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|
Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
|
the integers as multiples of the given timedelta unit.
|
|
Parameters
|
----------
|
data : numpy.ndarray with integer-dtype
|
unit : str, default "ns"
|
The timedelta unit to treat integers as multiples of.
|
|
Returns
|
-------
|
numpy.ndarray : timedelta64[ns] array converted from data
|
bool : whether a copy was made
|
FrR Tz timedelta64[r¦ r útimedelta64[ns])rz r rO r rs r r )r rh ry Ú dtype_strs rD ru ru F s ð IØÐ#4¨Dà zzRXXÒ ð {{288Ó$Ø à t|Ø" 4 &¨Ð* ØyyÓ#ä" 4¬|Ô<ð ð
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|
Convert a object-dtyped or string-dtyped array into an
|
timedelta64[ns]-dtyped array.
|
|
Parameters
|
----------
|
data : ndarray or Index
|
unit : str, default "ns"
|
The timedelta unit to treat integers as multiples of.
|
Must not be specified if the data contains a str.
|
errors : {"raise", "coerce", "ignore"}, default "raise"
|
How to handle elements that cannot be converted to timedelta64[ns].
|
See ``pandas.to_timedelta`` for details.
|
|
Returns
|
-------
|
numpy.ndarray : timedelta64[ns] array converted from data
|
|
Raises
|
------
|
ValueError : Data cannot be converted to timedelta64[ns].
|
|
Notes
|
-----
|
Unlike `pandas.to_timedelta`, if setting `errors=ignore` will not cause
|
errors to be ignored; they are caught and subsequently ignored at a
|
higher level.
|
r rp r| )r r Úobject_r rs )r rh rq rA rB s rD rt rt n s6 ô< ZZ¤B§J¡JÔ /Fä ! &¨t¸FÔ CFØ ;;Ð(Ó )Ð)rF c óÜ t | « } | t j d« k( r d}t |« t j
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