pandas.tseries.offsets.BusinessHour

class pandas.tseries.offsets.BusinessHour

DateOffset subclass representing possibly n business hours.

Parameters:

nint, default 1

The number of hours represented.

normalizebool, default False

Normalize start/end dates to midnight before generating date range.

startstr, time, or list of str/time, default “09:00”

Start time of your custom business hour in 24h format.

endstr, time, or list of str/time, default: “17:00”

End time of your custom business hour in 24h format.

offsettimedelta, default timedelta(0)

Time offset to apply.

Examples

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

>>> ts = pd.Timestamp(2022, 12, 9, 8)
>>> ts + pd.offsets.BusinessHour(n=5)
Timestamp('2022-12-09 14:00:00')

You can also change the start and the end of business hours.

>>> ts = pd.Timestamp(2022, 8, 5, 16)
>>> ts + pd.offsets.BusinessHour(start="11:00")
Timestamp('2022-08-08 11:00:00')

>>> from datetime import time as dt_time
>>> ts = pd.Timestamp(2022, 8, 5, 22)
>>> ts + pd.offsets.BusinessHour(end=dt_time(19, 0))
Timestamp('2022-08-08 10:00:00')

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

>>> ts = pd.Timestamp(2022, 12, 9, 8)
>>> ts + pd.offsets.BusinessHour(normalize=True)
Timestamp('2022-12-09 00:00:00')

You can divide your business day hours into several parts.

>>> import datetime as dt
>>> freq = pd.offsets.BusinessHour(start=["06:00", "10:00", "15:00"],
...                                end=["08:00", "12:00", "17:00"])
>>> pd.date_range(dt.datetime(2022, 12, 9), dt.datetime(2022, 12, 13), freq=freq)
DatetimeIndex(['2022-12-09 06:00:00', '2022-12-09 07:00:00',
               '2022-12-09 10:00:00', '2022-12-09 11:00:00',
               '2022-12-09 15:00:00', '2022-12-09 16:00:00',
               '2022-12-12 06:00:00', '2022-12-12 07:00:00',
               '2022-12-12 10:00:00', '2022-12-12 11:00:00',
               '2022-12-12 15:00:00', '2022-12-12 16:00:00'],
               dtype='datetime64[ns]', freq='bh')

Attributes

base	Returns a copy of the calling offset object with n=1 and all other attributes equal.
calendar
end
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	Returns a integer of the total number of nanoseconds for fixed frequencies.
next_bday	Used for moving to next business day.
normalize
offset	Alias for self._offset.
rule_code	Return a string representing the base frequency.
start
weekmask

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(other)	Roll provided date backward to next offset only if not on offset.
rollforward(other)	Roll provided date forward to next offset only if not on offset.