💡 Problem Formulation: When dealing with time series data in Python, analysts and developers often need to calculate the next business day given a certain datetime. Using pandas’ CustomBusinessHour offset object, one can shift a DateTimeIndex to the next business day, accommodating custom work schedules. This article provides various methods for achieving this, ensuring that the result respects weekends and holidays specific to a given locale. For instance, given an input datetime 2023-05-26 16:30:00 which is a Friday, the desired output would be the following business day, which typically would be 2023-05-29 09:00:00.
Method 1: Using Basic CustomBusinessHour
This method involves creating an instance of the CustomBusinessHour offset object from the pandas library. It requires specifying the work hours along with a holiday calendar to account for non-business days due to holidays. This method is both straightforward and flexible, allowing for clear definition of working hours and holidays.
Here’s an example:
from pandas.tseries.offsets import CustomBusinessHour from pandas.tseries.holiday import USFederalHolidayCalendar cbh = CustomBusinessHour(start='09:00', end='17:00', calendar=USFederalHolidayCalendar()) next_business_day = '2023-05-26 16:30:00' + cbh print(next_business_day)
The output of this code snippet will be:
2023-05-29 09:00:00
This code adds a CustomBusinessHour offset to a given datetime, considering US Federal holidays. The defined business hours are from 9:00 to 17:00. By adding the offset to the datetime of 2023-05-26 16:30:00, which lies beyond the end of the workday, the operation respects the weekend and lands on the next available business day and time.
Method 2: Using the rollforward Function
The rollforward function from pandas can be used to move the date to the next valid date in a CustomBusinessHour range. If the initial date is already on a valid date, it will remain unchanged. This is helpful when we need to ensure a date falls on a business day but don’t want to change it if it already does.
Here’s an example:
from pandas.tseries.offsets import CustomBusinessHour
from pandas.tseries.holiday import USFederalHolidayCalendar
cbh = CustomBusinessHour(calendar=USFederalHolidayCalendar())
next_business_day = cbh.rollforward('2023-05-26 16:30:00')
print(next_business_day)The output of this code snippet will be:
2023-05-29 09:00:00
This snippet uses rollforward, which checks if the provided datetime is outside business hours and if so, it rolls it forward to the start of the next business day. Here, it’s set to find the next business day following the US Federal Holiday Calendar, which in this example is the following Monday at 9:00 am.
Method 3: CustomBusinessHour with next_bday()
Another way is to combine pandas’ CustomBusinessHour with the BDay (business day) function. This allows for a fine-grained approach when simply finding the next business day, without specific hour constraints from ‘CustomBusinessHour’, is required.
Here’s an example:
from pandas.tseries.offsets import CustomBusinessHour, BDay
from pandas.tseries.holiday import USFederalHolidayCalendar
next_business_day = (BDay(calendar=USFederalHolidayCalendar()).next_bday('2023-05-26 16:30:00').normalize()
+ CustomBusinessHour(start='09:00', calendar=USFederalHolidayCalendar()))
print(next_business_day)The output of this code snippet will be:
2023-05-29 09:00:00
This code first finds the next business day using BDay then normalizes it to midnight, before adding the CustomBusinessHour offset to start at the defined work start time on the next business day.
Method 4: Adding CustomBusinessHour Until Valid Business Day
If the need is to ensure that we always move to the start of the next business day, regardless of the current time, we can add a loop that keeps adding an hour using CustomBusinessHour until we reach a valid starting business hour.
Here’s an example:
from pandas.tseries.offsets import CustomBusinessHour
from pandas.tseries.holiday import USFederalHolidayCalendar
cbh = CustomBusinessHour(start='09:00', end='17:00', calendar=USFederalHolidayCalendar())
current_time = '2023-05-26 16:30:00'
while not (current_time.hour == cbh.start.hour and current_time.minute == 0):
current_time += cbh
print(current_time)The output of this code snippet will be:
2023-05-29 09:00:00
This code continually adds a CustomBusinessHour to the current time until it reaches the start of the next business day. Unlike method 1, this can add multiple hours if needed, but will always result in the start of a new business day.
Bonus One-Liner Method 5: Leveraging next_bday() with normalize()
If the goal is simply to find the beginning of the next business day, a straightforward approach combines using BDay with the normalize() method. The combination effectively skips to the next business day at midnight, which then can be adjusted if needed.
Here’s an example:
from pandas.tseries.offsets import BDay
next_business_day = BDay().next_bday('2023-05-26 16:30:00').normalize()
print(next_business_day)The output of this code snippet will be:
2023-05-29 00:00:00
This line creates a BDay offset, finds the next business day using next_bday(), and then normalizes the time to midnight of that business day.
Summary/Discussion
- Method 1: Basic CustomBusinessHour. Straightforward and easy to adjust for holidays and work hours, but requires knowing the business hours in advance.
- Method 2: Using the rollforward Function. Useful to adjust dates without changing valid business days. Not as direct when business hours need to be considered beyond the default.
- Method 3: CustomBusinessHour with next_bday(). Combines business day calculation with specific start times, providing flexibility. More steps required for the operation.
- Method 4: Adding CustomBusinessHour Until Valid Business Day. Guaranteed to find the next starting business hour, but can be less efficient due to the potential loop.
- Method 5: Leveraging next_bday() with normalize(). Quick and clean for moving to the next business day at midnight, but requires additional adjustment for specific work hours.