pandas.tseries.offsets.Minute#

class pandas.tseries.offsets.Minute#

Offset n minutes.

Attributes

n	(int, default 1) The number of minutes represented.

See also

Examples

You can use the parameter n to represent a shift of n minutes.

>>> from pandas.tseries.offsets import Minute
>>> ts = pd.Timestamp(2022, 12, 9, 15)
>>> ts
Timestamp('2022-12-09 15:00:00')

>>> ts + Minute(n=10)
Timestamp('2022-12-09 15:10:00')
>>> ts - Minute(n=10)
Timestamp('2022-12-09 14:50:00')

>>> ts + Minute(n=-10)
Timestamp('2022-12-09 14:50:00')

Attributes

`base`	Returns a copy of the calling offset object with n=1 and all other attributes equal.
`freqstr`	Return a string representing the frequency.
`kwds`	Return a dict of extra parameters for the offset.
`n`
`name`	Return a string representing the base frequency.
`nanos`	Returns an integer of the total number of nanoseconds.
`normalize`
`rule_code`	Return a string representing the base frequency.

Methods

`copy`()	Return a copy of the frequency.
`is_month_end`(ts)	Return boolean whether a timestamp occurs on the month end.
`is_month_start`(ts)	Return boolean whether a timestamp occurs on the month start.
`is_on_offset`(dt)	Return boolean whether a timestamp intersects with this frequency.
`is_quarter_end`(ts)	Return boolean whether a timestamp occurs on the quarter end.
`is_quarter_start`(ts)	Return boolean whether a timestamp occurs on the quarter start.
`is_year_end`(ts)	Return boolean whether a timestamp occurs on the year end.
`is_year_start`(ts)	Return boolean whether a timestamp occurs on the year start.
`rollback`(dt)	Roll provided date backward to next offset only if not on offset.
`rollforward`(dt)	Roll provided date forward to next offset only if not on offset.