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.
Return a string representing the frequency.
Return a dict of extra parameters for the offset.
Return a string representing the base frequency.
Returns a integer of the total number of nanoseconds for fixed frequencies.
offset
Alias for self._offset.
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.