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

pandas.Series.to_period — pandas 2.3.1 documentation

Series.to_period(freq=None, copy=None)[source]#

Convert Series from DatetimeIndex to PeriodIndex.

Parameters:

freqstr, default None

Frequency associated with the PeriodIndex.

copybool, default True

Whether or not to return a copy.

Note

The copy keyword will change behavior in pandas 3.0. Copy-on-Write 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:

Series

Series with index converted to PeriodIndex.

Examples

>>> idx = pd.DatetimeIndex(['2023', '2024', '2025'])
>>> s = pd.Series([1, 2, 3], index=idx)
>>> s = s.to_period()
>>> s
2023    1
2024    2
2025    3
Freq: Y-DEC, dtype: int64

Viewing the index

>>> s.index
PeriodIndex(['2023', '2024', '2025'], dtype='period[Y-DEC]')

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