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Classe « DataFrame »

Méthode pandas.DataFrame.to_period

Signature de la méthode to_period

def to_period(self, freq: 'Frequency | None' = None, axis: 'Axis' = 0, copy: 'bool | None' = None) -> 'DataFrame' 

Description

help(DataFrame.to_period)

Convert DataFrame from DatetimeIndex to PeriodIndex.

Convert DataFrame from DatetimeIndex to PeriodIndex with desired
frequency (inferred from index if not passed).

Parameters
----------
freq : str, default
    Frequency of the PeriodIndex.
axis : {0 or 'index', 1 or 'columns'}, default 0
    The axis to convert (the index by default).
copy : bool, default True
    If False then underlying input data is not copied.

    .. note::
        The `copy` keyword will change behavior in pandas 3.0.
        `Copy-on-Write
        <https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html>`__
        will be enabled by default, which means that all methods with a
        `copy` keyword will use a lazy copy mechanism to defer the copy and
        ignore the `copy` keyword. The `copy` keyword will be removed in a
        future version of pandas.

        You can already get the future behavior and improvements through
        enabling copy on write ``pd.options.mode.copy_on_write = True``

Returns
-------
DataFrame
    The DataFrame has a PeriodIndex.

Examples
--------
>>> idx = pd.to_datetime(
...     [
...         "2001-03-31 00:00:00",
...         "2002-05-31 00:00:00",
...         "2003-08-31 00:00:00",
...     ]
... )

>>> idx
DatetimeIndex(['2001-03-31', '2002-05-31', '2003-08-31'],
dtype='datetime64[ns]', freq=None)

>>> idx.to_period("M")
PeriodIndex(['2001-03', '2002-05', '2003-08'], dtype='period[M]')

For the yearly frequency

>>> idx.to_period("Y")
PeriodIndex(['2001', '2002', '2003'], dtype='period[Y-DEC]')

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