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B �5�gl� � @ s d dl mZ d dlmZ d dlmZ d dlZd dlm Z m Z d dl m Z d dl mZmZmZmZmZmZmZmZmZ d dlmZmZ d d lmZ d d l m Z m Z m Z d d l m!Z!m"Z" d d l#m$Z% d d l&m'Z' d dl(m)Z)m*Z*m+Z+m,Z,m-Z-m.Z.m/Z/m0Z0m1Z1m2Z2 d dl3m4Z4 d dl5m6Z6m7Z7 d dl8m9Z9 d dl:m;Z; d dl<m=Z= d dl>m?Z?m@Z@mAZB d dlCmDZD d dlEmF mGZH d dlImJZJ d dlKmLZL e�r�d dlMmNZN d dl>mOZOmPZP dddd�d d �ZQG d d � d eBjR�ZSd0d"d#d$�d%d&�ZTd1d(d)�ZUd2d*d+�ZVd,d-�d.d/�ZWdS )3� )� annotations)� timedelta)� TYPE_CHECKINGN)�lib�tslibs)� NDArrayBacked) � BaseOffset�NaT�NaTType�Period�Tick� Timedelta� Timestamp�iNaT� to_offset)�ensure_timedelta64ns�precision_from_unit)�get_timedelta_field)�array_to_timedelta64�ints_to_pytimedelta�parse_timedelta_unit)�DtypeObj�NpDtype)�function)�astype_td64_unit_conversion) � DT64NS_DTYPE� TD64NS_DTYPE�is_dtype_equal�is_float_dtype�is_integer_dtype�is_object_dtype� is_scalar�is_string_dtype�is_timedelta64_dtype� pandas_dtype)�DatetimeTZDtype)�ABCCategorical� ABCMultiIndex)�isna)�nanops)�checked_add_with_arr)�ExtensionArray� IntegerArray� datetimelike)�generate_regular_range)� extract_array)�unpack_zerodim_and_defer)� DataFrame)� DatetimeArray� PeriodArray�str)�name�alias� docstringc s. dd�� fdd� }| |_ d|� d�|_t|�S )Nz np.ndarray)�returnc s* | j }t|� �}| jr&| j|d dd�}|S )N�float64)� fill_value�convert)�asi8r �_hasnans�_maybe_mask_results)�self�values�result)r6 � �S/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/arrays/timedeltas.py�fQ s z_field_accessor.<locals>.f� )�__name__�__doc__�property)r5 r6 r7 rD rB )r6 rC �_field_accessorP s rI c sZ e Zd ZU dZdZeZeej e fZ e Z dZdZg Zded< g Zded< dgZded < d d d d gZded< ee e Zded< dddddgZded< dd�dd�Zedd�dd ��Zd Zee j d fd d �d!d"�Z e d efd#d$d d%�� fd&d'� �Z e ed d(�d d d)�d*d+��Z!e ed e j d fd d d)�d,d-��Z"e d�d.d/��Z#d�d d0d1�d2d3�Z$dd�d4d5�Z%d�d d6d1�d7d8�Z&d�d d �d:d;�Z'd<d=� Z(d d d d d d9d>d?�d@dAd d dBdC�dDdE�Z)d d d dFd d9dG�d@dAdBd d dH�dIdJ�Z*d�d dK�dLdM�Z+e,j-d�d#d�dOdP��Z.dQdR� Z/dSdTdU�dVdW�Z0dXdY� Z1dZd�d[d\�Z2� fd]d^�Z3e4d_�d d�d`da��Z5e5Z6e4db�dcdd� �Z7e4de�dfdg� �Z8e4dh�didj� �Z9e4dk�dldm� �Z:e4dn�dodp� �Z;e4dq�drds� �Z<e4dt�dudv� �Z=e4dw�dxdy� �Z>d d�dzd{�Z?d d�d|d}�Z@d d�d~d�ZAd#d�d�d��ZBd#d�d�d��ZCeDd d d��ZEeDd d d��ZFeDd d d��ZGeDd d d��ZHed�d�d�d���ZI� ZJS )��TimedeltaArraya� 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 Ztimedeltaarray)r � timedelta64i� z list[str]� _other_ops� _bool_ops�freq� _object_ops�days�seconds� microseconds� nanoseconds� _field_ops�_datetimelike_ops�to_pytimedelta� total_seconds�round�floor�ceil�_datetimelike_methodszTimedelta | NaTType)r8 c C s t |dd�S )N�ns)�unit)r )r? �xrB rB rC � _box_func� s zTimedeltaArray._box_funcznp.dtypec C s t 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 )r )r? rB rB rC �dtype� s zTimedeltaArray.dtypeNF�bool)�copyc C sj t |dd�}t|t�r&|jdtjd�}t|dd �}|d k}|tjk rH|nd }t|t | ��r�|r`n6|d krp|j }n&|r�|j r�t |�}t � ||j d�\}}|j}t|tj�s�dt |�j� d�}t|��|jd kr�td ��|jd kr�|�t�}t|j� t|�}|d k�rd }t|��|�r |�� }|�r,t |�}tj| ||d� || _|d k�rf|d k �rft | �� | |� d S )NT)� extract_numpy�int64)�na_value�_freqFzUnexpected type 'zZ'. 'values' must be a TimedeltaArray, ndarray, or Series or Index containing one of those.)� � z.Only 1-dimensional input arrays are supported.�i8ZinferzUFrequency inference not allowed in TimedeltaArray.__init__. Use 'pd.array()' instead.)r@ r` ) r/ � isinstancer, �to_numpyr r �getattrr � no_default�typerN r �dtl�validate_inferred_freq�_ndarray�np�ndarrayrF � ValueError�ndimr` �viewr �_validate_td64_dtyperb r �__init__rf �_validate_frequency) r? r@ r` rN rb � inferred_freq� explicit_none�_�msgrB rB rC rx � sF zTimedeltaArray.__init__z np.ndarrayzBaseOffset | None)r@ rN r8 c sP |t kst|��t|tj�s(tt|���|jt ks6t�t� j|t d�}||_ |S )N)r@ r` ) r �AssertionErrorrj rr rs rn r` �super� _simple_newrf )�clsr@ rN r` rA )� __class__rB rC r� � s zTimedeltaArray._simple_new)r` rb )rb r8 c C s> |r t |� t||d d�\}}t�d |d�\}}| j||d�S )N)rb r] F)rN )rw �sequence_to_td64nsro rp r� )r� �datar` rb rz rN r| rB rB rC �_from_sequence� s z TimedeltaArray._from_sequencec C s� |r t |� |d k}|tjk r"|nd }t�|�\}}t|||d�\}}t�|||�\}}|r`d }| j||d�} |d kr�|d k r�| �| |� n|r�t | j �| _ | S )N)rb r] )rN ) rw r rm ro Zmaybe_infer_freqr� rp r� ry r rz rf ) r� r� r` rb rN r] r{ Z freq_inferrz rA rB rB rC �_from_sequence_not_strict s z(TimedeltaArray._from_sequence_not_strictc C s� t �|�}|d kr2tdd� |||gD ��r2td��t�||||�dkrNtd��|d k r^t|�}|d k rnt|�}t �|�\}}|d k r�t||||�}nt � |j |j |�� d�}|s�|dd � }|s�|d d� }| j |�d �|d �S ) Nc s s | ]}|d kV qd S )NrB )�.0r^ rB rB rC � <genexpr>, s z1TimedeltaArray._generate_range.<locals>.<genexpr>z1Must provide freq argument if no data is supplied� zVOf the four parameters: start, end, periods, and freq, exactly three must be specifiedri rg ���zm8[ns])rN )ro Zvalidate_periods�anyrt �comZcount_not_noner Zvalidate_endpointsr. rr Zlinspace�value�astyper� rv ) r� �start�endZperiodsrN �closedZ left_closedZ right_closed�indexrB rB rC �_generate_range( s& z TimedeltaArray._generate_rangeznp.timedelta64)�setitemr8 c C s8 t || j�s |tk r td��| j||d� t�|jd�S )Nz 'value' should be a Timedelta.)r� r\ )rj � _scalar_typer rt �_check_compatible_withrr rK r� )r? r� r� rB rB rC � _unbox_scalarL s z TimedeltaArray._unbox_scalarc C s t |�S )N)r )r? r� rB rB rC �_scalar_from_stringR s z"TimedeltaArray._scalar_from_string�Nonec C s d S )NrB )r? �otherr� rB rB rC r� U s z%TimedeltaArray._check_compatible_withTc C s4 t |�}|jdkr"t| j||d�S tjj| ||d�S )N�m)rb )r$ �kindr rq ro ZDatetimeLikeArrayMixinr� )r? r` rb rB rB rC r� \ s zTimedeltaArray.astypec c s� | j dkr,x�tt| ��D ]}| | V qW nh| j}t| �}d}|| d }xHt|�D ]<}|| }t|d | |�}t|||� dd�}|E d H qTW d S )Nrg i' T)�box)ru �range�lenr< �minr ) r? �ir� �length� chunksize�chunksZstart_iZend_iZ convertedrB rB rC �__iter__h s zTimedeltaArray.__iter__r )�axisr` �out�keepdims�initial�skipna� min_countz int | NonezNpDtype | None�int)r� r` r� r� r� c C s6 t �d||||d�� tj| j|||d�}| �||�S )NrB )r` r� r� r� )r� r� r� )�nvZ validate_sumr) Znansumrq Z_wrap_reduction_result) r? r� r` r� r� r� r� r� rA rB rB rC �sum{ s zTimedeltaArray.sumrg )r� r` r� �ddofr� r� )r� r` r� r� r� c C sR t jd|||d�dd� tj| j|||d�}|d ks>| jdkrH| �|�S | �|�S )NrB )r` r� r� �std)�fname)r� r� r� rg )r� Zvalidate_stat_ddof_funcr) Znanstdrq ru r_ Z_from_backing_data)r? r� r` r� r� r� r� rA rB rB rC r� � s zTimedeltaArray.std)�boxedc C s ddl m} || dd�S )Nr )�get_format_timedelta64T)r� )�pandas.io.formats.formatr� )r? r� r� rB rB rC � _formatter� s zTimedeltaArray._formatterr c s2 ddl m} || j|�� t�� fdd�| jD ��S )Nr )r� c s g | ] }� |��qS rB rB )r� r^ )� formatterrB rC � <listcomp>� s z7TimedeltaArray._format_native_types.<locals>.<listcomp>)r� r� rq rr �array)r? Zna_repZ date_format�kwargsr� rB )r� rC �_format_native_types� s z#TimedeltaArray._format_native_typesc C s2 t |t�rt�tdt|�j� dt| �j� ���d S )Nzcannot add the type z to a )rj r r~ � TypeErrorrn rF )r? r� rB rB rC � _add_offset� s zTimedeltaArray._add_offsetr r3 )r� r8 c C s2 ddl m} t�|j| j�}|||jd�}|| S )z& Add a Period object. r )r3 )rN )Zpandas.core.arrays.periodr3 rr Z broadcast_toZordinal�shaperN )r? r� r3 Zi8valsZothrB rB rC � _add_period� s zTimedeltaArray._add_periodc C s( t |tj�r ddlm} ||�}|| S )zS Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. r )r2 )rj rr rs �pandas.core.arraysr2 )r? r� r2 rB rB rC �_add_datetime_arraylike� s z&TimedeltaArray._add_datetime_arrayliker2 c C s� ddl m} |tk st�t|�}|tkrD| j�d�t�� }||�S | j}t||j | j d�}| � |�}|j rxt |j d�nt}|||| jd�S )Nr )r2 zm8[ms])Zarr_mask)�tz)r` rN )r� r2 r r~ r r< rv Z to_datetime64r* r� �_isnanr> r� r% r rN )r? r� r2 rA ri r` rB rB rC �_add_datetimelike_scalar� s z'TimedeltaArray._add_datetimelike_scalarc sL yt � �||�S tk rF } ztdt| �j� ��|�W d d }~X Y nX d S )Nz+Cannot add/subtract non-tick DateOffset to )r �_addsub_object_array�AttributeErrorr� rn rF )r? r� �op�err)r� rB rC r� � s z#TimedeltaArray._addsub_object_array�__mul__c s� t � �rB�j� }d }�jd k r2t� �s2�j� }t��||d�S t� d�sVt�� �� t� �t��krxt � j �sxt d��t � j �r�� �fdd�t t���D �}t�|�}t��|�S �j� }t��|�S )N)rN r` z$Cannot multiply with unequal lengthsc s g | ]}�| � | �qS rB rB )r� �n)r� r? rB rC r� s z*TimedeltaArray.__mul__.<locals>.<listcomp>)r! rq rN r( rn �hasattrrr r� r� r# r` rt r r� )r? r� rA rN rB )r� r? rC r� � s zTimedeltaArray.__mul__� __truediv__c sx t || j�rHt|�}|tkr>tj| jtjd�}|�tj � |S | j | S t � |�r�| j | }d }| j d k rv| j j| }t| �||d�S t|d�s�t�|�}t|�t| �kr�td��n�t|j�r�| j | S t|j��r^| �� �|�� � � �fdd�tt���D �}t�|��| j�}t �|�}|dk�rF|�� }t| ��|��|j�}n|dk�rZ|� t �}|S | j | }t| �|�S d S ) N)r` )rN r` z*Cannot divide vectors with unequal lengthsc s g | ]}�| � | �qS rB rB )r� r� )�orav�sravrB rC r� : s z.TimedeltaArray.__truediv__.<locals>.<listcomp>r Zfloating) rj �_recognized_scalarsr r rr �emptyr� r9 �fill�nanrq r r! rN �deltarn r� r� r� rt r# r` r Zravelr� Zreshape� infer_dtyper� r� �float)r? r� rA rN �inferredZflatrB )r� r� rC r� sB zTimedeltaArray.__truediv__� __rtruediv__c s t � �j�rHt� �� � tkr>tj�jtjd�}|�tj � |S � �j S t � � �rrt dt� �j� dt��j� ���t� d�s�t�� �� t� �t��kr�td��n`t� j�r�� �j S t� j�r� �fdd�tt���D �}t�|�S t d� j� dt��j� ���d S ) N)r` zCannot divide z by r` z*Cannot divide vectors with unequal lengthsc s g | ]}� | �| �qS rB rB )r� r� )r� r? rB rC r� n s z/TimedeltaArray.__rtruediv__.<locals>.<listcomp>z data by )rj r� r r rr r� r� r9 r� r� rq r r! r� rn rF r� r� r� rt r# r` r r� )r? r� rA rB )r� r? rC r� L s* zTimedeltaArray.__rtruediv__� __floordiv__c s t � �r�t� �j�rVt� �� � tkrFtj�jtjd�}|� tj � |S � � �j �}|S �j � }t�|�jt� d }�jd k r��j� }|jdkr��jjdkr�d }t��|�d�|d�S t� d�s�t�� �� t� �t��kr�td���nt� j��rBt��� �� �j � j }�j� jB }|�� �r>|� tj�}t�||tj � |S t � j��r�� �fdd�t t���D �}t�|�}t j |d d �d k�r�t!|�\}}t��|�S |S t"� j��s�t#� j��r҈j � }t��|�S t$� dt� �j%�}t&d |� d t��j%� ���d S )N)r` r zm8[ns])rN r` z"Cannot divide with unequal lengthsc s g | ]}�| � | �qS rB rB )r� r� )r� r? rB rC r� � s z/TimedeltaArray.__floordiv__.<locals>.<listcomp>F)r� r zCannot divide z by )'r! rj r� r r rr r� r� r9 r� r� � __rfloordiv__rq r< �putmaskr� r rN Znanosrn rv r� r� r� rt r# r` r� r� r r� r r� r� r r rl rF r� )r? r� rA rN �maskr| r` rB )r� r? rC r� v sR zTimedeltaArray.__floordiv__r� c s` t � �rvt� �j�rVt� �� � tkrFtj�jtjd�}|� tj � |S � � �j �}|S t dt� �j� dt��j� ���t� d�s�t�� �� t� �t��kr�td��n�t� j�r�t��� �� � j�j }�j� jB }|�� r�|�tj�}t�||tj � |S t� j��r0� �fdd�t t���D �}t�|�}|S t � dt� �j�}t d|� dt��j� ���d S )N)r` zCannot divide z by r` z"Cannot divide with unequal lengthsc s g | ]}� | �| �qS rB rB )r� r� )r� r? rB rC r� � s z0TimedeltaArray.__rfloordiv__.<locals>.<listcomp>) r! rj r� r r rr r� r� r9 r� r� r� rq r� rn rF r� r� r� rt r# r` r< r� r� r� r� r r� rl )r? r� rA r� r` rB )r� r? rC r� � s: z TimedeltaArray.__rfloordiv__�__mod__c C s$ t || j�rt|�}| | | | S )N)rj r� r )r? r� rB rB rC r� � s zTimedeltaArray.__mod__�__rmod__c C s$ t || j�rt|�}||| | S )N)rj r� r )r? r� rB rB rC r� � s zTimedeltaArray.__rmod__� __divmod__c C s0 t || j�rt|�}| | }| || }||fS )N)rj r� r )r? r� �res1�res2rB rB rC r� � s zTimedeltaArray.__divmod__� __rdivmod__c C s0 t || j�rt|�}|| }||| }||fS )N)rj r� r )r? r� r� r� rB rB rC r� s zTimedeltaArray.__rdivmod__c C s2 | j d k r"t| �| j | j d�S t| �| j �S )N)rN )rN rn rq )r? rB rB rC �__neg__ s zTimedeltaArray.__neg__c C s t | �| j| jd�S )N)rN )rn rq rN )r? rB rB rC �__pos__ s zTimedeltaArray.__pos__c C s t | �t�| j��S )N)rn rr �absrq )r? rB rB rC �__abs__ s zTimedeltaArray.__abs__c C s | j d| j dd�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 ------- seconds : [ndarray, Float64Index, Series] When the calling object is a TimedeltaArray, the return type is ndarray. When the calling object is a TimedeltaIndex, the return type is a Float64Index. 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() Float64Index([0.0, 86400.0, 172800.0, 259200.00000000003, 345600.0], dtype='float64') g��&� .>N)r: )r> r< )r? rB rB rC rW s 7z TimedeltaArray.total_secondsc C s t �| j�S )z� Return Timedelta Array/Index as object ndarray of datetime.timedelta objects. Returns ------- timedeltas : ndarray[object] )r r r< )r? rB rB rC rV W s z TimedeltaArray.to_pytimedeltaz Number of days for each element.z>Number of seconds (>= 0 and less than 1 day) for each element.zFNumber of microseconds (>= 0 and less than 1 second) for each element.zJNumber of nanoseconds (>= 0 and less than 1 microsecond) for each element.r1 c sj ddl m} ddddddd g� | j}|r6� fd d ��nd d � �|�fd d�| D �� d�}|sf|�d�}|S )z� Return a dataframe of the components (days, hours, minutes, seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas. Returns ------- DataFrame r )r1 rP �hours�minutesrQ Z millisecondsrR rS c s t | �rtjgt� � S | jS )N)r( rr r� r� � components)r^ )�columnsrB rC rD � s z$TimedeltaArray.components.<locals>.fc S s | j S )N)r� )r^ rB rB rC rD � s c s g | ] }� |��qS rB rB )r� r^ )rD rB rC r� � s z-TimedeltaArray.components.<locals>.<listcomp>)r� rd )�pandasr1 r= r� )r? r1 ZhasnansrA rB )r� rD rC r� s s zTimedeltaArray.components)N)F)F)T)F)r N)KrF � __module__� __qualname__rG Z_typr r� r rr rK r r� r# Z_is_recognized_dtypeZ_infer_matchesZ__array_priority__rL �__annotations__rM rO rT rU r[ r_ rH r` rf r r rm rx � classmethodr� r� r� r� r� r� r� r� r� r� r� r� ro Z ravel_compatr� r� r� r� r� r� r0 r� �__rmul__r� r� r� r� r� r� r� r� r� r� r� rW rV rI rP rQ rR rS r� � __classcell__rB rB )r� rC rJ ` s� : # :*D3 9 rJ F�raisera z tuple[np.ndarray, Tick | None])rb r8 c C s� d}|dk rt |�}t| d�sDt�| �dkr4t| �} tj| dd�} n t| t�rXtd��n t | dd�} t| t �r~| j d t d �} n>t| tj tf�s�t�| �} n"t| t�r�| jj| jtd �j} d}t| t�r�| j}t| j�s�t| j�r�t| ||d �} d}n�t | j��r t | |d �\} }|�o| }n�t | j��r�t� | �}t |�p>d�\}}| �!tj"�} | | } |�rlt�#| |�} | | | | �!tj"� �$d�} t | |< d}n8t%| j��r�| jt&k�r�t'| �} d}ntd| j� d���tj| |d�} | jdk�s�t(| ��| |fS )a� 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. Nr` r F)rb z0Cannot create a DatetimeArray from a MultiIndex.T)rc rd )re )r: )r] �errors)r] r\ ztimedelta64[ns]zdtype z' cannot be converted to timedelta64[ns]zm8[ns]))r r� rr ru �listr� rj r' r� r/ r, rk r rs r+ Zasarrayr& � categoriesZtake�codesr Z_valuesrJ rN r r` r" �objects_to_td64nsr �ints_to_td64nsr �isnanr r� rd rX rv r# r r r~ ) r� rb r] r� rz � copy_mader� r� �p�base�fracrB rB rC r� � sV ! r� r\ c C sn d}|dk r|nd}| j tjkr0| �tj�} d}|dkr\d|� d�}| �|�} t| �} d}n | �d�} | |fS )a� 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 FNr\ Tz timedelta64[�]ztimedelta64[ns])r` rr rd r� rv r )r� r] r� Z dtype_strrB rB rC r� s r� c C s* t j| t jdd�}t|||d�}|�d�S )aR 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. F)r` rb )r] r� ztimedelta64[ns])rr r� Zobject_r rv )r� r] r� r@ rA rB rB rC r� , s r� r )r8 c C sB t | �} t| t�d��r$d}t|��t| t�s>td| � d���| S )NrK zhPassing in 'timedelta' dtype with no precision is not allowed. Please pass in 'timedelta64[ns]' instead.zdtype z' cannot be converted to timedelta64[ns])r$ r rr r` rt r )r` r} rB rB rC rw P s rw )FNr� )r\ )Nr� )X� __future__r �datetimer �typingr �numpyrr Z pandas._libsr r Zpandas._libs.arraysr Zpandas._libs.tslibsr r r r r r r r r Z pandas._libs.tslibs.conversionr r Zpandas._libs.tslibs.fieldsr Z pandas._libs.tslibs.timedeltasr r r Zpandas._typingr r Zpandas.compat.numpyr r� Zpandas.core.dtypes.castr Zpandas.core.dtypes.commonr r r r r r r! r" r# r$ Zpandas.core.dtypes.dtypesr% Zpandas.core.dtypes.genericr& r' Zpandas.core.dtypes.missingr( Z pandas.corer) Zpandas.core.algorithmsr* r� r+ r, r- ro Zpandas.core.arrays._rangesr. Zpandas.core.common�core�commonr� Zpandas.core.constructionr/ Zpandas.core.ops.commonr0 r� r1 r2 r3 rI Z TimelikeOpsrJ r� r� r� rw rB rB rB rC �<module> sL , 0 Fd ( $
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