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.

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.
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.
next_bday	Used for moving to next business day.
offset	Alias for self._offset.

calendar
end
holidays
n
nanos
normalize
rule_code
start
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(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.