pandas.tseries.offsets.BusinessMonthBegin#

class pandas.tseries.offsets.BusinessMonthBegin#

DateOffset of one month at the first business day.

BusinessMonthBegin goes to the next date which is the first business day of the month.

See also

Examples

>>> ts = pd.Timestamp(2022, 11, 30)
>>> ts + pd.offsets.BMonthBegin()
Timestamp('2022-12-01 00:00:00')

>>> ts = pd.Timestamp(2022, 12, 1)
>>> ts + pd.offsets.BMonthBegin()
Timestamp('2023-01-02 00:00:00')

If you want to get the start of the current business month:

>>> ts = pd.Timestamp(2022, 12, 1)
>>> pd.offsets.BMonthBegin().rollback(ts)
Timestamp('2022-12-01 00:00:00')

Attributes

n	(int, default 1) The number of months represented.
normalize	(bool, default False) Normalize start/end dates to midnight before generating date range.

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`
`normalize`
`rule_code`

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.