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Int64Index)�get_op_result_namez PeriodIndex or list of Periods)Z target_klassc K sJ |j d�}|jdkr:|j dd �}t||d�}| j|f|�S | |f|�S d S )N�data�int64�freq)r, )�pop�dtyper � _simple_new)�cls�d�valuesr, � r3 �</tmp/pip-build-5_djhm0z/pandas/pandas/core/indexes/period.py�_new_PeriodIndex4 s
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�Zed[eed�dd��Zedd� �Zedd� �Zdefed�dd�Zdd� Ze e d�dd �Z d d � Z ed d � �Z ee!j"�e#e d!�d"d#��Z"e$e%d$�d%d&��Z&d\d'd(�Z'e(j)e(j)d)�d*d+�Z*ee!j+�d]� fd-d.� �Z+ee d$�d/d0��Z,eed$�d1d2��Z-e.e/d3 e0 �d^d4d5��Z1e.e/d6 e0 �d7d8� �Z2d_d9d:�Z3eed;�d<d=�Z4e5e6d>�d?d@�Z7e5dA�dBdC�Z8d`ee e dD�dEdF�Z9dGdH� Z:dadJdK�Z;� fdLdM�Z<edN�dOdP�Z=dbdQdR�Z>dcdSdT�Z?� fdUdV�Z@dd� fdWdX� ZA� ZBS )e� PeriodIndexa�
Immutable ndarray holding ordinal values indicating regular periods in time.
Index keys are boxed to Period objects which carries the metadata (eg,
frequency information).
Parameters
----------
data : array-like (1d int np.ndarray or PeriodArray), optional
Optional period-like data to construct index with.
copy : bool
Make a copy of input ndarray.
freq : str or period object, optional
One of pandas period strings or corresponding objects.
year : int, array, or Series, default None
month : int, array, or Series, default None
quarter : int, array, or Series, default None
day : int, array, or Series, default None
hour : int, array, or Series, default None
minute : int, array, or Series, default None
second : int, array, or Series, default None
tz : object, default None
Timezone for converting datetime64 data to Periods.
dtype : str or PeriodDtype, default None
Attributes
----------
day
dayofweek
dayofyear
days_in_month
daysinmonth
end_time
freq
freqstr
hour
is_leap_year
minute
month
quarter
qyear
second
start_time
week
weekday
weekofyear
year
Methods
-------
asfreq
strftime
to_timestamp
See Also
--------
Index : The base pandas Index type.
Period : Represents a period of time.
DatetimeIndex : Index with datetime64 data.
TimedeltaIndex : Index of timedelta64 data.
period_range : Create a fixed-frequency PeriodIndex.
Examples
--------
>>> idx = pd.PeriodIndex(year=[2000, 2002], quarter=[1, 3])
>>> idx
PeriodIndex(['2000Q1', '2002Q3'], dtype='period[Q-DEC]', freq='Q-DEC')
Z periodindex�namer, FTN�E)�how�returnc C s" | j j||�}t| �j|| jd�S )N)r< )�_data�asfreq�typer/ r< )�selfr, r> �arrr3 r3 r4 rA � s zPeriodIndex.asfreqc K s dddddddh} t |�j| �sBtt |�| �d }
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zPeriodIndex.__new__)r2 r< c C sF t |t�stt|���tj| �}||_|j|_||_i |_ |j
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Create a new PeriodIndex.
Parameters
----------
values : PeriodArray
Values that can be converted to a PeriodArray without inference
or coercion.
) rP r �AssertionErrorrB �objectrW r@ Z _index_datar< �_cacheZ_reset_identity)r0 r2 r< �resultr3 r3 r4 r/ � s
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_shallow_copy s zPeriodIndex._shallow_copyc C sx t |ttjttjf�r4t | jt�rj| jj|�}|S n6t |t �r^|j
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Convert timedelta-like input to an integer multiple of self.freq
Parameters
----------
other : timedelta, np.timedelta64, DateOffset, int, np.ndarray
Returns
-------
converted : int, np.ndarray[int64]
Raises
------
IncompatibleFrequency : if the input cannot be written as a multiple
of self.freq. Note IncompatibleFrequency subclasses ValueError.
N)rP r rQ Z timedelta64r
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�r�d|j kr�d|j � d�}t
|��t|�r�|S t| �|| j| jd�S ) z�
Gets called after a ufunc. Needs additional handling as
PeriodIndex stores internal data as int dtype
Replace this to __numpy_ufunc__ in future version
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|�}|j� }d||dk|j| j| k @ < |S )zc
where : array of timestamps
mask : array of booleans where data is not NA
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Get integer location for requested label.
Parameters
----------
key : Period, NaT, str, or datetime
String or datetime key must be parsable as Period.
Returns
-------
loc : int or ndarray[int64]
Raises
------
KeyError
Key is not present in the index.
TypeError
If key is listlike or otherwise not hashable.
zCannot interpret 'z ' as periodN�B)r, )r� r� )r r rP �str�_get_string_slicerN ry r r, r rn r �
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zPeriodIndex.get_loc)r� �kindc C s� |d ks t �t|t�r$t|| jd�S t|t�r�y:t|| j�\}}tj|�}| j ||�}||dkrddnd S t
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If label is a string or a datetime, cast it to Period.ordinal according
to resolution.
Parameters
----------
label : object
side : {'left', 'right'}
kind : {'loc', 'getitem'}
Returns
-------
bound : Period or object
Notes
-----
Value of `side` parameter should be validated in caller.
r� �getitem)r, r| r rr N�slice)r� r� )rX rP r r r, r� r r r� �_parsed_string_to_boundsry rn r r Z_invalid_indexer)rC �labelr� r� �parsedr� Zboundsr� r3 r3 r4 �_maybe_cast_slice_bound s
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|| jd�}t | �j
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||dd�S )N�O)r� r � intersection)r� ) r� r� r" �equalsZ_get_reconciled_name_objectr r. rf r� r r� )rC rb r� �thisr3 r3 r4 r� � s
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difference)r� )r� r� r" r� rB r/ r@ r< r rf rY r� r. r r� )rC rb r� r3 r3 r4 r� � s
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||dd�S )N)r� r� �_union)r� ) rt r� r� r� rP rB rX r r. rf r� )rC rb r� r� )r� r3 r4 r� � s
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__module__� __qualname__�__doc__Z_typ� _attributesZ_is_numeric_dtyper r@ r r, �libindexZ PeriodEngineZ _engine_typeZ!_supports_partial_string_indexingr rA r� rW � classmethodr r/ �propertyr2 r\ r r^ rd r
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Return a fixed frequency PeriodIndex.
The day (calendar) is the default frequency.
Parameters
----------
start : str or period-like, default None
Left bound for generating periods.
end : str or period-like, default None
Right bound for generating periods.
periods : int, default None
Number of periods to generate.
freq : str or DateOffset, optional
Frequency alias. By default the freq is taken from `start` or `end`
if those are Period objects. Otherwise, the default is ``"D"`` for
daily frequency.
name : str, default None
Name of the resulting PeriodIndex.
Returns
-------
PeriodIndex
Notes
-----
Of the three parameters: ``start``, ``end``, and ``periods``, exactly two
must be specified.
To learn more about the frequency strings, please see `this link
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
Examples
--------
>>> pd.period_range(start='2017-01-01', end='2018-01-01', freq='M')
PeriodIndex(['2017-01', '2017-02', '2017-03', '2017-04', '2017-05', '2017-06',
'2017-07', '2017-08', '2017-09', '2017-10', '2017-11', '2017-12',
'2018-01'],
dtype='period[M]', freq='M')
If ``start`` or ``end`` are ``Period`` objects, they will be used as anchor
endpoints for a ``PeriodIndex`` with frequency matching that of the
``period_range`` constructor.
>>> pd.period_range(start=pd.Period('2017Q1', freq='Q'),
... end=pd.Period('2017Q2', freq='Q'), freq='M')
PeriodIndex(['2017-03', '2017-04', '2017-05', '2017-06'],
dtype='period[M]', freq='M')
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