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

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_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.