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B �5�gO� � @ s d dl mZ d dlmZ d dlZd dlmZmZmZm Z d dl Z d dl m Z d dlmZmZmZmZmZmZmZmZmZmZ d dlm Z d dl m Z d d l m Z m!Z! d d l"m#Z#m$Z$m%Z%m&Z&m'Z' d d l(m)Z)m*Z*m+Z+ d d l,m-Z-m.Z. d d l/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5m6Z6m7Z7 d dl8m9Z9 d dl:m;Z;m<Z<m=Z=m>Z> d dl?m@Z@mAZA d dlBmC mDZE d dlFmGZH d dlImC mJZK e�r�d dlFmLZL ddiZMd1dd�dd�ZNG dd� deHjO�ZPdd� ZQd2d d d dd �d!d"�ZRd#d$� ZSd3d%d&�Zd4d(d)�ZTd5d*d+�d,d-�ZUd.d+�d/d0�ZVdS )6� )� annotations)� timedeltaN)� TYPE_CHECKING�Any�Callable�Sequence)� NDArrayBacked) � BaseOffset�NaT�NaTType� Timedelta�delta_to_nanoseconds�dt64arr_to_periodarr�iNaT�parsing�period� to_offset)� FreqGroup)�isleapyear_arr)�Tick� delta_to_tick)�DIFFERENT_FREQ�IncompatibleFrequency�Period�get_period_field_arr�period_asfreq_arr)� AnyArrayLike�Dtype�NpDtype)�cache_readonly�doc)� TD64NS_DTYPE� ensure_object�is_datetime64_dtype�is_dtype_equal�is_float_dtype�is_integer_dtype�is_period_dtype� pandas_dtype)� PeriodDtype)�ABCIndex�ABCPeriodIndex� ABCSeries�ABCTimedeltaArray)�isna�notna)� datetimelike)� DatetimeArray�klass� PeriodArray�str)�namec s � fdd�}� |_ ||_t|�S )Nc s | j j}t� | j|�}|S )N)�freq�_period_dtype_coder �asi8)�self�base�result)r5 � �O/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/arrays/period.py�fU s z_field_accessor.<locals>.f)�__name__�__doc__�property)r5 Z docstringr> r< )r5 r= �_field_accessorT s rB c s� e Zd ZU dZdZdZeZefZe Z dZ g Z de d< dgZde d< d d d gZde d < d ddddddddddddddd d gZde d < ee e Zde d < d d!d"gZde d#< d$e d%< d�d(d)d*�d+d,�Zed�d-d.d(d d/�d0d1��Zed&d'd*�d2d3d(d)d d4�d5d6��Zed&d'd*�d(d)d d7�d8d9��Zed�d d:�d;d<��Zed=d>� �Zd�d?d)d@dA�dBdC�ZdDdEdF�dGdH�Zd�d)dI�dJdK�Z e d$d:�dLdM��Z e dNd:�dOdP��Z d�dQd-dR�dSdT�Z!d�dUdV�Z"e#d dW�Z$e#ddX�Z%e#ddY�Z&e#ddZ�Z'e#dd[�Z(e#dd\�Z)e#dd]�Z*e*Z+e#dd^�Z,e,Z-e-Z.e#dd_� Z/Z0e#dd`�Z1e#d�Z2e#d da�Z3e3Z4e d-d:�dbdc��Z5d�dDdedf�dgdh�Z6d�did dj�dkdl�Z7d?d:�dmdn�Z8e9f e:dododp���d�dDd df�drds��Z;d�d)dt�dudv�Z<e=j>d�d-d:�dxdy��Z?d�d)d{�� fd|d}� Z@d�d-d:�dd��ZAd�d d:�� fd�d�� ZBd�d�� ZCd�d�� ZDd�d�� ZEd-d�d d��d�d��ZFdNd��� fd�d�� ZG� fd�d��ZHd�d�� ZId�d�� ZJdid:�d�d��ZKe ded:�d�d���ZLe ded:�d�d���ZMd�d)d�d��d�d��ZN� ZOS )�r3 a) Pandas ExtensionArray for storing Period data. Users should use :func:`~pandas.period_array` to create new instances. Alternatively, :func:`~pandas.array` can be used to create new instances from a sequence of Period scalars. Parameters ---------- values : Union[PeriodArray, Series[period], ndarray[int], PeriodIndex] The data to store. These should be arrays that can be directly converted to ordinals without inference or copy (PeriodArray, ndarray[int64]), or a box around such an array (Series[period], PeriodIndex). dtype : PeriodDtype, optional A PeriodDtype instance from which to extract a `freq`. If both `freq` and `dtype` are specified, then the frequencies must match. freq : str or DateOffset The `freq` to use for the array. Mostly applicable when `values` is an ndarray of integers, when `freq` is required. When `values` is a PeriodArray (or box around), it's checked that ``values.freq`` matches `freq`. copy : bool, default False Whether to copy the ordinals before storing. Attributes ---------- None Methods ------- None See Also -------- Period: Represents a period of time. PeriodIndex : Immutable Index for period data. period_range: Create a fixed-frequency PeriodArray. array: Construct a pandas array. Notes ----- There are two components to a PeriodArray - ordinals : integer ndarray - freq : pd.tseries.offsets.Offset The values are physically stored as a 1-D ndarray of integers. These are called "ordinals" and represent some kind of offset from a base. The `freq` indicates the span covered by each element of the array. All elements in the PeriodArray have the same `freq`. i� Z periodarray)r z list[str]� _other_ops� is_leap_year� _bool_ops� start_time�end_timer6 � _object_ops�year�month�day�hour�minute�second� weekofyear�weekday�week� dayofweek� day_of_week� dayofyear� day_of_year�quarter�qyear� days_in_month� daysinmonth� _field_ops�_datetimelike_ops�strftime� to_timestamp�asfreq�_datetimelike_methodsr) �_dtypeNFz Dtype | None�bool)�dtype�copyc C s� t ||�}|d k r t�|�}t|t�rD|j}t|t| ��sTtd��nt|t�rT|j}t|t| ��r�|d k r~||j kr~t ||��|j |j }}t j |d|d�}|d kr�td��t�| |t|�� d S )NzIncorrect dtype�int64)rb rc z,freq is not specified and cannot be inferred)�validate_dtype_freqr �_maybe_convert_freq� isinstancer, �_values�type� TypeErrorr+ r6 �raise_on_incompatible�_ndarray�np�array� ValueErrorr �__init__r) )r9 �valuesrb r6 rc r< r< r= rp � s" zPeriodArray.__init__z np.ndarrayzBaseOffset | None)rq r6 rb �returnc C s0 d}t |tj�r|jdks"t|��| |||d�S )Nz Should be numpy array of type i8�i8)r6 rb )rg rm �ndarrayrb �AssertionError)�clsrq r6 rb Z assertion_msgr< r< r= � _simple_new� s zPeriodArray._simple_newztype[PeriodArray]z&Sequence[Period | None] | AnyArrayLike)rv �scalarsrb rc rr c C st |rt |t�r|j}nd }t || �r@t|j|� |r<|�� }|S tj|td�}|pZt � |�}t � ||�}| ||d�S )N)rb )r6 ) rg r) r6 re rb rc rm �asarray�object� libperiodZ extract_freqZextract_ordinals)rv rx rb rc r6 �periods�ordinalsr< r< r= �_from_sequence� s zPeriodArray._from_sequence)rb rc rr c C s | j |||d�S )N)rb rc )r~ )rv �stringsrb rc r< r< r= �_from_sequence_of_strings� s z%PeriodArray._from_sequence_of_strings)rr c C s t |||�\}}| ||d�S )a Construct a PeriodArray from a datetime64 array Parameters ---------- data : ndarray[datetime64[ns], datetime64[ns, tz]] freq : str or Tick tz : tzinfo, optional Returns ------- PeriodArray[freq] )r6 )r )rv �datar6 �tzr< r< r= �_from_datetime64 s z PeriodArray._from_datetime64c C s� t �|�}|d k r t�|�}t|�}|d k s4|d k rX|dkrDtd��t||||�\}}n(|dkrxtf d|i|��\}}ntd��||fS )Nr z=Can either instantiate from fields or endpoints, but not bothr6 z/Not enough parameters to construct Period range)�dtlZvalidate_periodsr rf �lenro �_get_ordinal_range�_range_from_fields)rv �start�endr| r6 �fieldsZ field_countZsubarrr< r< r= �_generate_range s zPeriodArray._generate_rangezPeriod | NaTTypeznp.int64)�value�setitemrr c C sN |t krt�|j�S t|| j�r:| j||d� t�|j�S td|� d���d S )N)r� z!'value' should be a Period. Got 'z ' instead.) r rm rd r� rg � _scalar_type�_check_compatible_with�ordinalro )r9 r� r� r< r< r= � _unbox_scalar0 s zPeriodArray._unbox_scalarr4 r )r� rr c C s t || jd�S )N)r6 )r r6 )r9 r� r< r< r= �_scalar_from_string> s z PeriodArray._scalar_from_string)r� c C s |t kr d S | �|� d S )N)r �_require_matching_freq)r9 �otherr� r< r< r= r� A s z"PeriodArray._check_compatible_withc C s | j S )N)r` )r9 r< r< r= rb I s zPeriodArray.dtyper c C s | j jS )zC Return the frequency object for this PeriodArray. )rb r6 )r9 r< r< r= r6 N s zPeriodArray.freqzNpDtype | None)rb rr c C s0 |dkr| j S |tkr | j S tjt| �td�S )Nrs )rb )r8 ra �_isnanrm rn �listrz )r9 rb r< r< r= � __array__U s zPeriodArray.__array__c C s� ddl }ddlm} |dk r�|j�|�r>|j| j| �� |d�S t||�rp| j |j kr�t d| j � d|j � d���nt d|� d ���|| j �}|j| j| �� d d�}|j � ||�S ) z6 Convert myself into a pyarrow Array. r N)�ArrowPeriodType)�maskri zENot supported to convert PeriodArray to array with different 'freq' (z vs �)z)Not supported to convert PeriodArray to 'z' typerd )�pyarrowZ pandas.core.arrays._arrow_utilsr� �types� is_integerrn rl r. rg �freqstrr6 rj ZExtensionArrayZ from_storage)r9 ri r� r� Z period_typeZ storage_arrayr< r< r= �__arrow_array__` s zPeriodArray.__arrow_array__z) The year of the period. z6 The month as January=1, December=12. z) The days of the period. z) The hour of the period. z+ The minute of the period. z+ The second of the period. z/ The week ordinal of the year. z> The day of the week with Monday=0, Sunday=6. z. The ordinal day of the year. z* The quarter of the date. z2 The number of days in the month. c C s t t�| j��S )zH Logical indicating if the date belongs to a leap year. )r rm ry rI )r9 r< r< r= rD � s zPeriodArray.is_leap_yearr� r1 )�howrr c C s� ddl m} t�|�}|dk}|rx|dks4| jdkrXtdd�tdd� }| jdd �| S tdd�}| | j jdd �| S |d kr�| �� }|}nt� |�}|j }| j ||d �}t� |j |�}||��d �S ) a� Cast to DatetimeArray/Index. Parameters ---------- freq : str or DateOffset, optional Target frequency. The default is 'D' for week or longer, 'S' otherwise. how : {'s', 'e', 'start', 'end'} Whether to use the start or end of the time period being converted. Returns ------- DatetimeArray/Index r )r1 �E�B� �D�nsr� )r� NZinfer)�pandas.core.arraysr1 r{ �validate_end_aliasr6 r r] �_get_to_timestamp_baser rf r7 r^ Zperiodarr_to_dt64arrr8 Z _with_freq) r9 r6 r� r1 r� �adjustr: Znew_parr�new_datar< r< r= r] � s" zPeriodArray.to_timestamp�int)r| rr c C sR |dk r t dt| �j� d���| j|| jj }| jr@t|| j< t| �|| jd�S )a� Shift each value by `periods`. Note this is different from ExtensionArray.shift, which shifts the *position* of each element, padding the end with missing values. Parameters ---------- periods : int Number of periods to shift by. freq : pandas.DateOffset, pandas.Timedelta, or str Frequency increment to shift by. Nz%`freq` argument is not supported for z ._time_shift)r6 ) rj ri r? r8 r6 �n�_hasnansr r� )r9 r| r6 rq r< r< r= � _time_shift� s zPeriodArray._time_shiftc C s t j|| jd�S )N)r� r6 )r Z _from_ordinalr6 )r9 �xr< r< r= � _box_func s zPeriodArray._box_funcZ PeriodIndex)r� Z other_namer� c C sx t �|�}t�|�}| jj}|j}| j}|dk}|rF|| jj d }n|}t||||�}| j rht || j < t | �||d�S )a� Convert the {klass} to the specified frequency `freq`. Equivalent to applying :meth:`pandas.Period.asfreq` with the given arguments to each :class:`~pandas.Period` in this {klass}. Parameters ---------- freq : str A frequency. how : str {{'E', 'S'}}, default 'E' Whether the elements should be aligned to the end or start within pa period. * 'E', 'END', or 'FINISH' for end, * 'S', 'START', or 'BEGIN' for start. January 31st ('END') vs. January 1st ('START') for example. Returns ------- {klass} The transformed {klass} with the new frequency. See Also -------- {other}.asfreq: Convert each Period in a {other_name} to the given frequency. Period.asfreq : Convert a :class:`~pandas.Period` object to the given frequency. Examples -------- >>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A') >>> pidx PeriodIndex(['2010', '2011', '2012', '2013', '2014', '2015'], dtype='period[A-DEC]') >>> pidx.asfreq('M') PeriodIndex(['2010-12', '2011-12', '2012-12', '2013-12', '2014-12', '2015-12'], dtype='period[M]') >>> pidx.asfreq('M', how='S') PeriodIndex(['2010-01', '2011-01', '2012-01', '2013-01', '2014-01', '2015-01'], dtype='period[M]') r� r� )r6 ) r{ r� r rf r6 r7 r8 r� r r� r r� ri ) r9 r6 r� Zbase1Zbase2r8 r� r� r� r< r< r= r^ s . zPeriodArray.asfreq)�boxedc C s |rt S djS )Nz'{}')r4 �format)r9 r� r< r< r= � _formatter\ s zPeriodArray._formatterr c s| | � t�}� r � fdd��ndd� �| jr`| j}|||< | }t��fdd�|| D ��||< nt��fdd�|D ��}|S )z3 actually format my specific types c s | � � �S )N)r\ )�dt)� date_formatr< r= �<lambda>k � z2PeriodArray._format_native_types.<locals>.<lambda>c S s t | �S )N)r4 )r� r< r< r= r� m r� c s g | ] }� |��qS r< r< )�.0r� )� formatterr< r= � <listcomp>s s z4PeriodArray._format_native_types.<locals>.<listcomp>c s g | ] }� |��qS r< r< )r� r� )r� r< r= r� u s )�astyperz r� r� rm rn )r9 Zna_repr� �kwargsrq r� Zimaskr< )r� r� r= �_format_native_typesa s "z PeriodArray._format_native_typesT)rc c sH t |�}t|| j�r$|s | S | �� S t|�r8| �|j�S t� j||d�S )N)rc ) r( r$ r` rc r' r^ r6 �superr� )r9 rb rc )� __class__r< r= r� z s zPeriodArray.astype�leftc C s, | � |��d�}| j�d�}|j|||d�S )NzM8[ns])�side�sorter)Z _validate_searchsorted_value�viewrl � searchsorted)r9 r� r� r� Zm8arrr< r< r= r� � s zPeriodArray.searchsortedc s@ |d k r.| � d�}|j|||d�}|� | j�S t� j|||d�S )NzM8[ns])r� �method�limit)r� �fillnarb r� )r9 r� r� r� Zdtar; )r� r< r= r� � s zPeriodArray.fillnac C s |t k s t�tS )N)r ru �NotImplemented)r9 r� r< r< r= � _sub_datelike� s zPeriodArray._sub_datelikec sF � � |� � j}||j }t�� fdd�|D ��}� jrBt|� j< |S )Nc s g | ]}� j | �qS r< )r6 )r� r� )r9 r< r= r� � s z+PeriodArray._sub_period.<locals>.<listcomp>)r� r8 r� rm rn r� r r� )r9 r� r8 r� r< )r9 r= � _sub_period� s zPeriodArray._sub_periodc sb � � |� tj� j|j � j|jd�}t�� fdd�|D ��}� jsJ|jr^� j|jB }t||< |S )a� Subtract a Period Array/Index from self. This is only valid if self is itself a Period Array/Index, raises otherwise. Both objects must have the same frequency. Parameters ---------- other : PeriodIndex or PeriodArray Returns ------- result : np.ndarray[object] Array of DateOffset objects; nulls represented by NaT. )�arr_maskZb_maskc s g | ]}� j j| �qS r< )r6 r: )r� r� )r9 r< r= r� � s z1PeriodArray._sub_period_array.<locals>.<listcomp>) r� �algos�checked_add_with_arrr8 r� rm rn r� r )r9 r� � new_valuesr� r< )r9 r= �_sub_period_array� s z PeriodArray._sub_period_arrayzCallable[[Any, Any], Any])r� �oprr c C sd |t jt jgkst�|t jkr$| }tj| j|| jd�}|�d�}t � || jt � t | �|| j d�S )a% Add or subtract array of integers; equivalent to applying `_time_shift` pointwise. Parameters ---------- other : np.ndarray[integer-dtype] op : {operator.add, operator.sub} Returns ------- result : PeriodArray )r� rs )r6 )�operator�add�subru r� r� r8 r� r� rm Zputmaskr ri r6 )r9 r� r� Z res_valuesr< r< r= �_addsub_int_array� s z PeriodArray._addsub_int_array)r� c s< t |t�rt�| j|dd� t� �|j�}t| �|| jd�S )NT)r: )r6 ) rg r ru r� r� �_add_timedeltalike_scalarr� ri r6 )r9 r� r; )r� r< r= � _add_offset� s zPeriodArray._add_offsetc s4 t | jt�st| |��t|�r(| �|�}t� �|�S )z� Parameters ---------- other : timedelta, Tick, np.timedelta64 Returns ------- PeriodArray )rg r6 r rk r/ � _check_timedeltalike_freq_compatr� r� )r9 r� )r� r< r= r� � s z%PeriodArray._add_timedeltalike_scalarc C sf t | jt�s td| j� ���t�t|��s6| �|�}n| t� d� S | � |t j �j }t| �|| jd�S )z� Parameters ---------- other : TimedeltaArray or ndarray[timedelta64] Returns ------- result : ndarray[int64] z2Cannot add or subtract timedelta64[ns] dtype from r )rb )rg r6 r rj rb rm �allr. r� � timedelta64r� r� r� r8 ri )r9 r� �deltar} r< r< r= �_add_timedelta_arraylike s z$PeriodArray._add_timedelta_arraylikec C s� t | jt�st�| jjj}t |ttjtf�r6t |�}nBt |tj �rr|j j dksRt�|j t krf|�t �}|�d�}n|j}t�|| dk�r�|| }|S t| |��dS )a< Arithmetic operations with timedelta-like scalars or array `other` are only valid if `other` is an integer multiple of `self.freq`. If the operation is valid, find that integer multiple. Otherwise, raise because the operation is invalid. Parameters ---------- other : timedelta, np.timedelta64, Tick, ndarray[timedelta64], TimedeltaArray, TimedeltaIndex Returns ------- multiple : int or ndarray[int64] Raises ------ IncompatibleFrequency �mrs r N)rg r6 r ru r: �nanosr rm r� r rt rb �kindr! r� r� r8 r� rk )r9 r� Z base_nanosr� r� r< r< r= r� s z,PeriodArray._check_timedeltalike_freq_compatc C sH | j j}|tjjk r tjjS tjj| kr8tjjkrDn ntjjS |S )a Return frequency code group used for base of to_timestamp against frequency code. Return day freq code against longer freq than day. Return second freq code against hour between second. Returns ------- int )r` Z _dtype_coder ZFR_BUSr� ZFR_DAYZFR_HRZFR_SEC)r9 r: r< r< r= r� L s z"PeriodArray._get_to_timestamp_basec C s | j dd�S )Nr� )r� )r] )r9 r< r< r= rF _ s zPeriodArray.start_timec C s | j dd�S )Nr� )r� )r] )r9 r< r< r= rG c s zPeriodArray.end_time�None)r: rr c C s^ t |t�r|}n|j}|r*| jj|jk}n | j|k}|rZtjt| �j| j|jd�}t |��d S )N)rv �own_freq� other_freq) rg r r6 r: r r� ri r? r� r )r9 r� r: r� � condition�msgr< r< r= r� g s z"PeriodArray._require_matching_freq)NNF)NN)N)F)F)N)N)Nr� )N)Nr� )F)r N)T)r� N)NNN)F)Pr? � __module__� __qualname__r@ Z__array_priority__Z_typr r� Z_recognized_scalarsr' Z_is_recognized_dtypeZ_infer_matchesrC �__annotations__rE rH rZ r[ r_ rp � classmethodrw r~ r� r� r� r� r� r� r rb rA r6 r� r� rB rI rJ rK rL rM rN rO rQ rS rR rP rT rU rV rW rX rY rD r] r� r� r �_shared_doc_kwargsr^ r� r� Z ravel_compatr� r� r� r� r� r� r� r� r� r� r� r� r� rF rG r� � __classcell__r< r< )r� r= r3 _ s� 5 ,F 3c C sf t |tjtf�s|dkr d}n(t |ttttf�r8|j}nt t |��j}t j t | �j| j|d�}t|�S )a> Helper function to render a consistent error message when raising IncompatibleFrequency. Parameters ---------- left : PeriodArray right : None, DateOffset, Period, ndarray, or timedelta-like Returns ------- IncompatibleFrequency Exception to be raised by the caller. N)rv r� r� )rg rm rt r- r+ r3 r r r� r r r r� ri r? r )r� �rightr� r� r< r< r= rk | s rk Fz,Sequence[Period | str | None] | AnyArrayLikezstr | Tick | Nonera )r� r6 rc rr c C s� t | dd�}t|�r t�| |�S t|�r4t| |d�S t| tjtt t f�sPt| �} t� | �}|rht |�}nd}t |�r�t|�dkr�td��t|j�r�|jtjdd�}t�||�}t||d�S t|�} tj| |d�S ) a� Construct a new PeriodArray from a sequence of Period scalars. Parameters ---------- data : Sequence of Period objects A sequence of Period objects. These are required to all have the same ``freq.`` Missing values can be indicated by ``None`` or ``pandas.NaT``. freq : str, Tick, or Offset The frequency of every element of the array. This can be specified to avoid inferring the `freq` from `data`. copy : bool, default False Whether to ensure a copy of the data is made. Returns ------- PeriodArray See Also -------- PeriodArray pandas.PeriodIndex Examples -------- >>> period_array([pd.Period('2017', freq='A'), ... pd.Period('2018', freq='A')]) <PeriodArray> ['2017', '2018'] Length: 2, dtype: period[A-DEC] >>> period_array([pd.Period('2017', freq='A'), ... pd.Period('2018', freq='A'), ... pd.NaT]) <PeriodArray> ['2017', '2018', 'NaT'] Length: 3, dtype: period[A-DEC] Integers that look like years are handled >>> period_array([2000, 2001, 2002], freq='D') <PeriodArray> ['2000-01-01', '2001-01-01', '2002-01-01'] Length: 3, dtype: period[D] Datetime-like strings may also be passed >>> period_array(['2000-Q1', '2000-Q2', '2000-Q3', '2000-Q4'], freq='Q') <PeriodArray> ['2000Q1', '2000Q2', '2000Q3', '2000Q4'] Length: 4, dtype: period[Q-DEC] rb N)r6 r z9PeriodIndex does not allow floating point in constructionF)rc )rb )�getattrr# r3 r� r' rg rm rt r� �tupler, ry r) r% r� rj r& rb r� rd r{ Z from_ordinalsr" r~ )r� r6 rc Z data_dtypeZarrdatarb Zarrr} r< r< r= � period_array� s& : r� c C sV |dk rt |�}| dk rRt| �} t| �s0td��|dkr@| j}n|| jkrRtd��|S )at If both a dtype and a freq are available, ensure they match. If only dtype is available, extract the implied freq. Parameters ---------- dtype : dtype freq : DateOffset or None Returns ------- freq : DateOffset Raises ------ ValueError : non-period dtype IncompatibleFrequency : mismatch between dtype and freq Nzdtype must be PeriodDtypez&specified freq and dtype are different)r r( r' ro r6 r )rb r6 r< r< r= re � s re c C s� | j t� d�kr td| j � ���|dkr^t| t�rB| j| j } }qrt| t�rr| j| jj } }nt| ttf�rr| j} t � |�}|j }t | � d�||�|fS )a� Convert an datetime-like array to values Period ordinals. Parameters ---------- data : Union[Series[datetime64[ns]], DatetimeIndex, ndarray[datetime64ns]] freq : Optional[Union[str, Tick]] Must match the `freq` on the `data` if `data` is a DatetimeIndex or Series. tz : Optional[tzinfo] Returns ------- ordinals : ndarray[int64] freq : Tick The frequency extracted from the Series or DatetimeIndex if that's used. zM8[ns]z Wrong dtype: Nrs )rb rm ro rg r* rh r6 r, r� r rf r7 �c_dt64arr_to_periodarrr� )r� r6 r� r: r< r< r= r s r r� c C sH t �| ||�dkrtd��|d k r0t|�}|j}| d k rBt| |�} |d k rTt||�}t| t�}t|t�}|r�|r�| j|jkr�td��| tks�|tkr�td��|d kr�|r�| j}n|r�|j}ntd��|d k �r$|| }| d k�rt j |j | | |j d |t j d�}n t j | j | j | |t j d�}n t j | j |j d |t j d�}||fS )N� zOOf the three parameters: start, end, and periods, exactly two must be specifiedz!start and end must have same freqz start and end must not be NaTz#Could not infer freq from start/endr� )rb ) �comZcount_not_nonero r r� r rg r6 r rm Zaranger� rd )r� r� r| r6 ZmultZ is_start_perZ is_end_perr� r< r< r= r� = s> " r� z tuple[np.ndarray, BaseOffset])rr c C sX |d kr d}|d krd}|d kr$d}|d kr0d}g }|d k r�|d krVt d�}tjj} n&t |�}t�|�} | tjjkr|td��|j} t| |�\} }x�t | |�D ]>\} } t � | | | �\} } t� | | dddddd| � }|� |� q�W ndt |�}t�|�} t| |||||�}x>t |� D ]2\} }}}}}|� t� | |||||dd| � � �qW tj|tjd�|fS )Nr r� �Qzbase must equal FR_QTR)rb )r r ZFR_QTRr� r{ Zfreq_to_dtype_coderu r� �_make_field_arrays�zipr Zquarter_to_myearZperiod_ordinal�appendrm rn rd )rI rJ rV rK rL rM rN r6 r} r: r� �y�qr� �valZarraysZmth�d�hZmn�sr< r< r= r� m s: &r� zlist[np.ndarray]c sd d � xL| D ]D}t |ttjtf�r � d k r>t|�� kr>td��q � d kr t|�� q W � fdd�| D �S )Nz Mismatched Period array lengthsc s4 g | ],}t |tjttf�r$t�|�n t�|� ��qS r< )rg rm rt r� r, ry �repeat)r� r� )�lengthr< r= r� � s z&_make_field_arrays.<locals>.<listcomp>)rg r� rm rt r, r� ro )r� r� r< )r� r= r� � s r� )N)NF)N)r� )NNNNNNNN)W� __future__r �datetimer r� �typingr r r r �numpyrm Zpandas._libs.arraysr Zpandas._libs.tslibsr r r r r r r� r r r r{ r Zpandas._libs.tslibs.dtypesr Zpandas._libs.tslibs.fieldsr Zpandas._libs.tslibs.offsetsr r Zpandas._libs.tslibs.periodr r r r r Zpandas._typingr r r Zpandas.util._decoratorsr r Zpandas.core.dtypes.commonr! r" r# r$ r% r& r' r( Zpandas.core.dtypes.dtypesr) Zpandas.core.dtypes.genericr* r+ r, r- Zpandas.core.dtypes.missingr. r/ Zpandas.core.algorithms�coreZ algorithmsr� r� r0 r� Zpandas.core.common�commonr� r1 r� rB Z DatelikeOpsr3 rk r� re r� r� r� r< r< r< r= �<module> sZ 0 ( ## W! % 1 '
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