pandas.Series.to_timestamp#

Series.to_timestamp(freq=None, how='start', copy=None)[source]#

Cast to DatetimeIndex of Timestamps, at beginning of period.

Parameters:

freqstr, default frequency of PeriodIndex: Desired frequency.
how{‘s’, ‘e’, ‘start’, ‘end’}: Convention for converting period to timestamp; start of period vs. end.
copybool, default True: Whether or not to return a copy.

Returns:

Series with DatetimeIndex

Examples

>>> idx = pd.PeriodIndex(['2023', '2024', '2025'], freq='Y')
>>> s1 = pd.Series([1, 2, 3], index=idx)
>>> s1
2023    1
2024    2
2025    3
Freq: A-DEC, dtype: int64

The resulting frequency of the Timestamps is YearBegin

>>> s1 = s1.to_timestamp()
>>> s1
2023-01-01    1
2024-01-01    2
2025-01-01    3
Freq: AS-JAN, dtype: int64

Using freq which is the offset that the Timestamps will have

>>> s2 = pd.Series([1, 2, 3], index=idx)
>>> s2 = s2.to_timestamp(freq='M')
>>> s2
2023-01-31    1
2024-01-31    2
2025-01-31    3
Freq: A-JAN, dtype: int64