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Showing content from https://pandas.pydata.org/pandas-docs/stable/reference/api/../api/pandas.Series.dt.to_period.html below:

pandas.Series.dt.to_period — pandas 2.3.1 documentation

Series.dt.to_period(*args, **kwargs)[source]#

Cast to PeriodArray/PeriodIndex at a particular frequency.

Converts DatetimeArray/Index to PeriodArray/PeriodIndex.

Parameters:

freqstr or Period, optional

One of pandas’ period aliases or an Period object. Will be inferred by default.

Returns:

PeriodArray/PeriodIndex

Raises:

ValueError

When converting a DatetimeArray/Index with non-regular values, so that a frequency cannot be inferred.

Examples

>>> df = pd.DataFrame({"y": [1, 2, 3]},
...                   index=pd.to_datetime(["2000-03-31 00:00:00",
...                                         "2000-05-31 00:00:00",
...                                         "2000-08-31 00:00:00"]))
>>> df.index.to_period("M")
PeriodIndex(['2000-03', '2000-05', '2000-08'],
            dtype='period[M]')

Infer the daily frequency

>>> idx = pd.date_range("2017-01-01", periods=2)
>>> idx.to_period()
PeriodIndex(['2017-01-01', '2017-01-02'],
            dtype='period[D]')

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