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pandas.Timestamp.round — pandas 2.3.1 documentation

Timestamp.round(freq, ambiguous='raise', nonexistent='raise')#

Round the Timestamp to the specified resolution.

Parameters:

freqstr

Frequency string indicating the rounding resolution.

ambiguousbool 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.

Returns:

a new Timestamp rounded to the given resolution of freq

Raises:

ValueError if the freq cannot be converted

Notes

If the Timestamp has a timezone, rounding will take place relative to the local (“wall”) time and re-localized to the same timezone. When rounding 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 rounded using multiple frequency units:

>>> ts.round(freq='h') # hour
Timestamp('2020-03-14 16:00:00')

>>> ts.round(freq='min') # minute
Timestamp('2020-03-14 15:33:00')

>>> ts.round(freq='s') # seconds
Timestamp('2020-03-14 15:32:52')

>>> ts.round(freq='ms') # milliseconds
Timestamp('2020-03-14 15:32:52.193000')

freq can also be a multiple of a single unit, like ‘5min’ (i.e. 5 minutes):

>>> ts.round(freq='5min')
Timestamp('2020-03-14 15:35:00')

or a combination of multiple units, like ‘1h30min’ (i.e. 1 hour and 30 minutes):

>>> ts.round(freq='1h30min')
Timestamp('2020-03-14 15:00:00')

Analogous for pd.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 01:30:00").tz_localize("Europe/Amsterdam")

>>> ts_tz.round("h", ambiguous=False)
Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')

>>> ts_tz.round("h", ambiguous=True)
Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')

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