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.

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.
freqstr	Return a string representing the frequency.
kwds	Return a dict of extra parameters for the offset.
name	Return a string representing the base frequency.
offset	Alias for self._offset.

calendar
holidays
n
nanos
normalize
rule_code
weekmask

Methods

copy	Return a copy of the frequency.
is_anchored	Return boolean whether the frequency is a unit frequency (n=1).
is_month_end	Return boolean whether a timestamp occurs on the month end.
is_month_start	Return boolean whether a timestamp occurs on the month start.
is_on_offset	Return boolean whether a timestamp intersects with this frequency.
is_quarter_end	Return boolean whether a timestamp occurs on the quarter end.
is_quarter_start	Return boolean whether a timestamp occurs on the quarter start.
is_year_end	Return boolean whether a timestamp occurs on the year end.
is_year_start	Return boolean whether a timestamp occurs on the year start.
rollback	Roll provided date backward to next offset only if not on offset.
rollforward	Roll provided date forward to next offset only if not on offset.