pandas.tseries.offsets.BusinessDay

class pandas.tseries.offsets.BusinessDay

DateOffset subclass representing possibly n business days.

Parameters:

nint, default 1

The number of days represented.

normalizebool, default False

Normalize start/end dates to midnight.

offsettimedelta, default timedelta(0)

Time offset to apply.

Examples

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

>>> ts = pd.Timestamp(2022, 12, 9, 15)
>>> ts.strftime('%a %d %b %Y %H:%M')
'Fri 09 Dec 2022 15:00'
>>> (ts + pd.offsets.BusinessDay(n=5)).strftime('%a %d %b %Y %H:%M')
'Fri 16 Dec 2022 15:00'

Passing the parameter normalize equal to True, you shift the start of the next business day to midnight.

>>> ts = pd.Timestamp(2022, 12, 9, 15)
>>> ts + pd.offsets.BusinessDay(normalize=True)
Timestamp('2022-12-12 00:00:00')

Attributes

base	Returns a copy of the calling offset object with n=1 and all other attributes equal.
calendar
freqstr	Return a string representing the frequency.
holidays
kwds	Return a dict of extra parameters for the offset.
n
name	Return a string representing the base frequency.
nanos
normalize
offset	Alias for self._offset.
rule_code
weekmask

Methods

copy()	Return a copy of the frequency.
is_anchored()	(DEPRECATED) Return boolean whether the frequency is a unit frequency (n=1).
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.