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Return a new Timestamp floored to this resolution.
Parameters
----------
freq : str
Frequency string indicating the flooring resolution.
ambiguous : bool or {'raise', 'NaT'}, default 'raise'
The behavior is as follows:
* bool contains flags to determine if time is dst or not (note
that this flag is only applicable for ambiguous fall dst dates).
* 'NaT' will return NaT for an ambiguous time.
* 'raise' will raise an AmbiguousTimeError for an ambiguous time.
nonexistent : {'raise', 'shift_forward', 'shift_backward, 'NaT', timedelta}, default 'raise'
A nonexistent time does not exist in a particular timezone
where clocks moved forward due to DST.
* 'shift_forward' will shift the nonexistent time forward to the
closest existing time.
* 'shift_backward' will shift the nonexistent time backward to the
closest existing time.
* 'NaT' will return NaT where there are nonexistent times.
* timedelta objects will shift nonexistent times by the timedelta.
* 'raise' will raise an NonExistentTimeError if there are
nonexistent times.
Raises
------
ValueError if the freq cannot be converted.
Notes
-----
If the Timestamp has a timezone, flooring will take place relative to the
local ("wall") time and re-localized to the same timezone. When flooring
near daylight savings time, use ``nonexistent`` and ``ambiguous`` to
control the re-localization behavior.
Examples
--------
Create a timestamp object:
>>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
A timestamp can be floored using multiple frequency units:
>>> ts.floor(freq='h') # hour
Timestamp('2020-03-14 15:00:00')
>>> ts.floor(freq='min') # minute
Timestamp('2020-03-14 15:32:00')
>>> ts.floor(freq='s') # seconds
Timestamp('2020-03-14 15:32:52')
>>> ts.floor(freq='ns') # nanoseconds
Timestamp('2020-03-14 15:32:52.192548651')
``freq`` can also be a multiple of a single unit, like '5min' (i.e. 5 minutes):
>>> ts.floor(freq='5min')
Timestamp('2020-03-14 15:30:00')
or a combination of multiple units, like '1h30min' (i.e. 1 hour and 30 minutes):
>>> ts.floor(freq='1h30min')
Timestamp('2020-03-14 15:00:00')
Analogous for ``pd.NaT``:
>>> pd.NaT.floor()
NaT
When rounding near a daylight savings time transition, use ``ambiguous`` or
``nonexistent`` to control how the timestamp should be re-localized.
>>> ts_tz = pd.Timestamp("2021-10-31 03:30:00").tz_localize("Europe/Amsterdam")
>>> ts_tz.floor("2h", ambiguous=False)
Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')
>>> ts_tz.floor("2h", ambiguous=True)
Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')
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