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�

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ej(j$�d,d���Z						d-							d.d�Zeddddddddd�	d/d��Zedd�d/d��Ze	d0d��Zd1d�Zd2d�Zd3�fd�Ze	d4d��Ze	d5d��Z�fd�Zd �Z d6d!�Z!d7d"�Z"e
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    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

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    month : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    quarter : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    day : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    hour : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    minute : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    second : int, array, or Series, default None

        .. deprecated:: 2.2.0
           Use PeriodIndex.from_fields instead.
    dtype : str or PeriodDtype, default None

    Attributes
    ----------
    day
    dayofweek
    day_of_week
    dayofyear
    day_of_year
    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
    from_fields
    from_ordinals

    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.from_fields(year=[2000, 2002], quarter=[1, 3])
    >>> idx
    PeriodIndex(['2000Q1', '2002Q3'], dtype='period[Q-DEC]')
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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)rarro�timedelta64r�ndarrayr(r;� _check_timedeltalike_freq_compatr�base�nrr�int)rArE�deltas   r0�_maybe_convert_timedeltaz$PeriodIndex._maybe_convert_timedeltais���"�e�i�����r�z�z�J�K��$�)�)�T�*��
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        Get integer location for requested label.

        Parameters
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        key : Period, NaT, str, or datetime
            String or datetime key must be parsable as Period.

        Returns
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        zCannot interpret 'z' as periodN)�_check_indexing_errorrr*r	ra�str�_parse_with_resorn�KeyError�_can_partial_date_slice�_partial_date_slicerD�_cast_partial_indexing_scalarr
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�%��%��*��*�	�����)� ���	�;�
�;�	��	!�	!�"�>�#�>����	�	�	�	��6� ��6����	�	�	 �	 �!�8�"��8����	�	�	 �	 �!�8�"��8���
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	�	�	$�	$�%��&�r2r9c��tj|||�dk7rtd��|�"t|t�st|t�sd}tj||||�\}}t|�}t||��}t||��S)a
    Return a fixed frequency PeriodIndex.

    The day (calendar) is the default frequency.

    Parameters
    ----------
    start : str, datetime, date, pandas.Timestamp, or period-like, default None
        Left bound for generating periods.
    end : str, datetime, date, pandas.Timestamp, 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]')

    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]')
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