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eHe f eNeLd�dd�ZOd d � ZPd)d d �Zd*d!d"�ZQd+d#d$�ZRd%d&� ZSdS ),� )� timedeltaN)�Any�Callable�List�Optional�Sequence�Type�Union) �
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ABCIndexClass�ABCPeriodIndex� ABCSeries�ABCTimedeltaArray)�isna�notna)� datetimelike)�ExtensionArray)�namec s � fdd�}� |_ ||_t|�S )Nc s | j j}t� | j|�}|S )N)�freq�_period_dtype_coder �asi8)�self�base�result)r. � �;/tmp/pip-build-5_djhm0z/pandas/pandas/core/arrays/period.py�f8 s z_field_accessor.<locals>.f)�__name__�__doc__�property)r. Z docstringr7 r5 )r. r6 �_field_accessor7 s r; c s e Zd ZU dZdZdZeZefZe Z
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d@�Z5e/ddA�Z6e6Z7e/ddB�Z8e8Z9e/dCdD� Z:Z;e/ddE�Z<e/d�Z=e/ddF�Z>e>Z?e*ejd$�dGdH��Z@e*dIdJ� �ZAe*dKdL� �ZBddNdO�ZCd�dPdQ�ZDe*dRdS� �ZEd�e
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ZIdbdc� ZJddde� ZKdfdg� ZLejeMeNeNgeNf d dh�didj�ZOe+dk�� fdldm� ZP� fdndo�ZQdpdq� ZRdrds� ZSd�dudv�ZT� ZUS )�� PeriodArrayaT
Pandas ExtensionArray for storing Period data.
Users should use :func:`period_array` to create new instances.
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).
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`.
dtype : PeriodDtype, optional
A PeriodDtype instance from which to extract a `freq`. If both
`freq` and `dtype` are specified, then the frequencies must match.
copy : bool, default False
Whether to copy the ordinals before storing.
Attributes
----------
None
Methods
-------
None
See Also
--------
period_array : Create a new PeriodArray.
PeriodIndex : Immutable Index for period data.
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� is_leap_year�
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|d|d�}|| _ |d kr�td��t|�| _d S )NzIncorrect dtype�int64)�dtype�copyz,freq is not specified and cannot be inferred)�validate_dtype_freqr �_maybe_convert_freq�
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||�}| ||d�S )N)rS )r/ ) r/ rW rU rS rT r] �asarray�object� libperiodZ extract_freqZextract_ordinals)rg rj rS rT r/ �periods�ordinalsr5 r5 r6 �_from_sequence� s
zPeriodArray._from_sequence)rc c C s | j |||�S )N)rp )rg �stringsrS rT r5 r5 r6 �_from_sequence_of_strings� s z%PeriodArray._from_sequence_of_stringsc 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]
)r/ )r )rg �datar/ �tzr5 r5 r6 �_from_datetime64� s z PeriodArray._from_datetime64c C s� t j|�}|d k r tj|�}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 bothr/ z/Not enough parameters to construct Period range)�dtlZvalidate_periodsr rV �lenr_ �_get_ordinal_range�_range_from_fields)rg �start�endrn r/ �fieldsZ field_countZsubarrr5 r5 r6 �_generate_range� s
zPeriodArray._generate_range)�valuerc c C s> |t kr|jS t|| j�r*| j|� |jS td|� d���d S )Nz!'value' should be a Period. Got 'z
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_unbox_scalar s
zPeriodArray._unbox_scalarc C s t || jd�S )N)r/ )r r/ )r2 r~ r5 r5 r6 �_scalar_from_string
s z PeriodArray._scalar_from_string)�setitemc C s& |t kr d S | j|jkr"t| |��d S )N)r �freqstrr[ )r2 �otherr� r5 r5 r6 r�
s z"PeriodArray._check_compatible_withc C s | j S )N)r` )r2 r5 r5 r6 rS s zPeriodArray.dtypec C s | j jS )zC
Return the frequency object for this PeriodArray.
)rS r/ )r2 r5 r5 r6 r/ s zPeriodArray.freqc C s0 |dkr| j S |tkr | j S tjt| �td�S )Nrd )rS )r1 �bool�_isnanr] r^ �listrl )r2 rS r5 r5 r6 � __array__" s
zPeriodArray.__array__c C s� ddl }ddlm} |dk r�|jj|�r>|j| j| j� |d�S t||�rp| j |j
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Convert myself into a pyarrow Array.
r N)�ArrowPeriodType)�maskrY zENot supported to convert PeriodArray to array with different 'freq' (z vs �)z)Not supported to convert PeriodArray to 'z' typerR )�pyarrowZ pandas.core.arrays._arrow_utilsr� �types�
is_integerr^ r\ r* rW r� r/ rZ r- Z from_storage)r2 rY r� r� Z period_typeZ
storage_arrayr5 r5 r6 �__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.
� day_of_yearz.
The ordinal day of the year.
z*
The quarter of the date.
z2
The number of days in the month.
c C s t tj| j��S )zH
Logical indicating if the date belongs to a leap year.
)r r] rk r@ )r2 r5 r5 r6 r= � s zPeriodArray.is_leap_yearc C s | j dd�S )Nrz )�how)rP )r2 r5 r5 r6 r> � s zPeriodArray.start_timec C s | j dd�S )Nr{ )r� )rP )r2 r5 r5 r6 r? � s zPeriodArray.end_timerz c C s� ddl m} tj|�}|dk}|rx|dks4| jdkrXtdd�tdd� }| jdd �| S tdd�}| | j jdd �| S |d
kr�| j� }|}ntj |�}|j
}| j ||d �}tj |j
|�}||�jd �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
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DatetimeArray�E�B� �D�nsrz )r� NZinfer)�pandas.core.arraysr� rm �validate_end_aliasr/ r
rP Z_get_to_timestamp_baser rV r0 rQ Zperiodarr_to_dt64arrr1 Z
_with_freq)r2 r/ r� r� r{ �adjustr3 �new_datar5 r5 r6 rP � s"
zPeriodArray.to_timestampc 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)r/ ) rZ rY r8 r1 r/ �n�_hasnansr r� )r2 rn r/ ra r5 r5 r6 � _time_shift� s
zPeriodArray._time_shiftc s � fdd�S )Nc s t j| � jd�S )N)r� r/ )r Z
_from_ordinalr/ )�x)r2 r5 r6 �<lambda>� s z'PeriodArray._box_func.<locals>.<lambda>r5 )r2 r5 )r2 r6 � _box_func� s zPeriodArray._box_funcr� )r� rc c C sx t j|�}tj|�}| jj}|j}| j}|dk}|rF|| jj d }n|}t||||�}| j rht
|| j < t | �||d�S )an
Convert the Period Array/Index to the specified frequency `freq`.
Parameters
----------
freq : str
A frequency.
how : str {'E', 'S'}
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
-------
Period Array/Index
Constructed with the new 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]', freq='A-DEC')
>>> pidx.asfreq('M')
PeriodIndex(['2010-12', '2011-12', '2012-12', '2013-12', '2014-12',
'2015-12'], dtype='period[M]', freq='M')
>>> pidx.asfreq('M', how='S')
PeriodIndex(['2010-01', '2011-01', '2012-01', '2013-01', '2014-01',
'2015-01'], dtype='period[M]', freq='M')
r� r� )r/ )
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zPeriodArray.asfreq)�boxedc C s |rt S djS )Nz'{}')�str�format)r2 r� r5 r5 r6 �
_formatter& s zPeriodArray._formatterr c s| | j t�}� r � fdd��ndd� �| jr`| j}|||< | }tj�fdd�|| D ��||< ntj�fdd�|D ��}|S )z3
actually format my specific types
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| j � �S )N)rO )�dt)� date_formatr5 r6 r� 2 s z2PeriodArray._format_native_types.<locals>.<lambda>c S s t | �S )N)r� )r� r5 r5 r6 r� 4 s c s g | ] }� |��qS r5 r5 )�.0r� )� formatterr5 r6 �
<listcomp>: s z4PeriodArray._format_native_types.<locals>.<listcomp>c s g | ] }� |��qS r5 r5 )r� r� )r� r5 r6 r� < s )�astyperl r� r� r] r^ )r2 Zna_repr� rh ra r� Zimaskr5 )r� r� r6 �_format_native_types+ s
"z PeriodArray._format_native_typesT)rT c s, t |�}t|�r | j|j�S t� j||d�S )N)rT )r$ r# rQ r/ �superr� )r2 rS rT )� __class__r5 r6 r� A s zPeriodArray.astypec C s |t k s t�tS )N)r rf �NotImplemented)r2 r� r5 r5 r6 �
_sub_datelikeM s zPeriodArray._sub_datelikec sF � j |� � j}||j }tj� fdd�|D ��}� jrBt|� j< |S )Nc s g | ]}� j | �qS r5 )r/ )r� r� )r2 r5 r6 r� W s z+PeriodArray._sub_period.<locals>.<listcomp>)r� r1 r� r] r^ r� r r� )r2 r� r1 r� r5 )r2 r6 � _sub_periodQ s
zPeriodArray._sub_periodc s� � j |j kr.tjt� �j� j|jd�}t|��tj� j |j � j
|j
d�}t j � fdd�|D ��}� j
sn|j
r�� j
|j
B }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.
)rg �own_freq�
other_freq)�arr_maskZb_maskc s g | ]}� j j| �qS r5 )r/ r3 )r� r� )r2 r5 r6 r� w s z1PeriodArray._sub_period_array.<locals>.<listcomp>)r/ r r� rY r8 r� r �algos�checked_add_with_arrr1 r� r] r^ r� r )r2 r� �msgZ
new_valuesr� r5 )r2 r6 �_sub_period_array^ s z PeriodArray._sub_period_array)r� �oprc c C s^ |t jt jgkst�|t jkr$| }tj| j|| jd�}|jd�}t || j< t
| �|| j d�S )a%
Add or subtract array of integers; equivalent to applying
`_time_shift` pointwise.
Parameters
----------
other : np.ndarray[integer-dtype]
op : {operator.add, operator.sub}
Returns
-------
result : PeriodArray
)r� rd )r/ ) �operator�add�subrf r� r� r1 r� �viewr rY r/ )r2 r� r� Z
res_valuesr5 r5 r6 �_addsub_int_array} s
z PeriodArray._addsub_int_array)r� c sH t |t� st�|j| jjkr(t| |��t� j|j�}t | �|| jd�S )N)r/ )
rW r rf r3 r/ r[ r� �_add_timedeltalike_scalarr� rY )r2 r� r4 )r� r5 r6 � _add_offset� s
zPeriodArray._add_offsetc s4 t | jt�st| |��t|�r(| j|�}t� j|�S )z�
Parameters
----------
other : timedelta, Tick, np.timedelta64
Returns
-------
PeriodArray
)rW r/ r r[ r+ � _check_timedeltalike_freq_compatr� r� )r2 r� )r� r5 r6 r� � s
z%PeriodArray._add_timedeltalike_scalarc C sf t | jt�s td| j� ���tjt|��s6| j|�}n| tj d� S | j
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Parameters
----------
other : TimedeltaArray or ndarray[timedelta64]
Returns
-------
result : ndarray[int64]
z2Cannot add or subtract timedelta64[ns] dtype from r )rS )rW r/ r rZ rS r] �allr* r� � timedelta64r� r� r� r1 rY )r2 r� �deltaro r5 r5 r6 �_add_timedelta_arraylike� s
z$PeriodArray._add_timedelta_arraylikec C s� t | jt�st�| jjj}t |ttjtf�r6t |�}nBt |tj
�rr|j j dksRt�|j t
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�}|jd�}n|j}tj|| 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
�mrd r N)rW r/ r rf r3 �nanosr r] r� r re rS �kindr r� r� r1 r� r[ )r2 r� Z
base_nanosr� r� r5 r5 r6 r� � s
z,PeriodArray._check_timedeltalike_freq_compatr� c C s t j| |d�S )N)� na_sentinel)r- � factorize)r2 r� r5 r5 r6 r� s zPeriodArray.factorize)NNF)N)NF)NF)N)F)N)N)Nrz )N)Nr� )F)r N)T���)r� )Vr8 �
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r/ r� r� r; r@ rA rB rC rD rE rF rH rI rG rJ r� rK rL rM rN r= r> r? rP r� r� rQ r� r� r� r� r� r� r r r� r� r� r� r� r� �
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|��j}t j t
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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)rg r� r� )rW r] re r) r' r< r r
r� r r
r r� rY r8 r )�left�rightr� r� r5 r5 r6 r[ s r[ F)rs r/ rT rc c C s� t | dd�}t|�r tj| |�S t|�r2t| |�S t| tjtt t
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| �r�t| �dkr�td��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]
rS Nr z9PeriodIndex does not allow floating point in construction)rS )�getattrr! r< ru r# rW r] re r� �tupler( rk r% r" rw rZ r rp )rs r/ rT Z
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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# r_ r/ r )rS r/ r5 r5 r6 rU | s
rU c C s� | j tj d�kr td| j � ���|dkr\t| t�rB| j| j } }nt| t�r\| j| jj } }t j
|�}t| ttf�rz| j} |j }t | j
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[int]
freq : Tick
The frequency extracted from the Series or DatetimeIndex if that's
used.
zM8[ns]z
Wrong dtype: Nrd )rS r] r_ rW r& rX r/ r( r� r rV r0 �c_dt64arr_to_periodarrr� )rs r/ rt r3 r5 r5 r6 r � s
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