pandas.tseries.offsets.CustomBusinessHour

classpandas.tseries.offsets.CustomBusinessHour

DateOffset subclass representing possibly n custom business days.

In CustomBusinessHour we can use custom weekmask, holidays, and calendar.

Parameters:

n:int, default 1

The number of hours represented.

normalize:bool, default False

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

weekmask:str, Default ‘Mon Tue Wed Thu Fri’

Weekmask of valid business days, passed to numpy.busdaycalendar.

holidays:list

List/array of dates to exclude from the set of valid business days, passed to numpy.busdaycalendar.

calendar:np.busdaycalendar

Calendar to integrate.

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

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

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

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

offset:timedelta, default timedelta(0)

Time offset to apply.

Examples

In the example below the default parameters give the next business hour.

>>> ts = pd.Timestamp(2022, 8, 5, 16)
>>> ts + pd.offsets.CustomBusinessHour()
Timestamp('2022-08-08 09:00:00')

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

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

>>> from datetime import time as dt_time
>>> ts = pd.Timestamp(2022, 8, 5, 16)
>>> ts + pd.offsets.CustomBusinessHour(end=dt_time(19, 0))
Timestamp('2022-08-05 17:00:00')

>>> ts = pd.Timestamp(2022, 8, 5, 22)
>>> ts + pd.offsets.CustomBusinessHour(end=dt_time(19, 0))
Timestamp('2022-08-08 10:00:00')

You can divide your business day hours into several parts.

>>> import datetime as dt
>>> freq = pd.offsets.CustomBusinessHour(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='cbh')

Business days can be specified by weekmask parameter. To convert the returned datetime object to its string representation the function strftime() is used in the next example.

>>> import datetime as dt
>>> freq = pd.offsets.CustomBusinessHour(weekmask="Mon Wed Fri",
...                                      start="10:00", end="13:00")
>>> pd.date_range(dt.datetime(2022, 12, 10), dt.datetime(2022, 12, 18),
...               freq=freq).strftime('%a %d %b %Y %H:%M')
Index(['Mon 12 Dec 2022 10:00', 'Mon 12 Dec 2022 11:00',
       'Mon 12 Dec 2022 12:00', 'Wed 14 Dec 2022 10:00',
       'Wed 14 Dec 2022 11:00', 'Wed 14 Dec 2022 12:00',
       'Fri 16 Dec 2022 10:00', 'Fri 16 Dec 2022 11:00',
       'Fri 16 Dec 2022 12:00'],
       dtype='object')

Using NumPy business day calendar you can define custom holidays.

>>> import datetime as dt
>>> bdc = np.busdaycalendar(holidays=['2022-12-12', '2022-12-14'])
>>> freq = pd.offsets.CustomBusinessHour(calendar=bdc, start="10:00", end="13:00")
>>> pd.date_range(dt.datetime(2022, 12, 10), dt.datetime(2022, 12, 18), freq=freq)
DatetimeIndex(['2022-12-13 10:00:00', '2022-12-13 11:00:00',
               '2022-12-13 12:00:00', '2022-12-15 10:00:00',
               '2022-12-15 11:00:00', '2022-12-15 12:00:00',
               '2022-12-16 10:00:00', '2022-12-16 11:00:00',
               '2022-12-16 12:00:00'],
               dtype='datetime64[ns]', freq='cbh')

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
next_bday	Used for moving to next business day.
normalize
offset	Alias for self._offset.
rule_code
start
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(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.