5 Best Ways to Apply Weekmask on CustomBusinessHour Offset in Pandas

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πŸ’‘ Problem Formulation: When working with time series data in pandas, one might need to define custom business hours while also limiting operations to specific days of the week. For businesses with non-standard operating times or days, it’s crucial to configure a CustomBusinessHour object properly with a weekmask. Below, we explore how to apply a weekmask to a CustomBusinessHour offset, which is particularly useful for setting a custom frequency for business day calculations, potentially excluding weekends or other non-working days.

Method 1: Initializing CustomBusinessHour with a Weekmask

This method involves directly creating a CustomBusinessHour object with a weekmask that specifies the days of the week when the business is operational. The weekmask is a string containing ‘1’ for business days and ‘0’ for holidays. By passing this mask to the constructor, we can control the behavior of the offset.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour

# Define business hours from 9 AM to 5 PM, Monday to Friday
cbh = CustomBusinessHour(start='09:00', end='17:00',
                         weekmask='Mon Tue Wed Thu Fri')



Mon Tue Wed Thu Fri

This code snippet defines business hours that are valid from Monday to Friday, 9 AM to 5 PM, and prints the weekmask applied to the CustomBusinessHour object. The ‘weekmask’ attribute helps in restricting the business hours specifically to those days defined in the mask.

Method 2: Dynamically Modifying the Weekmask

After creating a CustomBusinessHour object, one might need to change the weekmask dynamically, depending on different conditions or user input. This can be done by assigning a new weekmask string to the weekmask attribute of the existing CustomBusinessHour object.

Here’s an example:

cbh.weekmask = 'Mon Wed Fri'



Mon Wed Fri

Here, the business hours were initially set for weekdays, but the requirement changed to operate only on Mondays, Wednesdays, and Fridays. We simply update the weekmask attribute accordingly, which is a flexible approach when business schedules change temporarily or permanently.

Method 3: Using Weekmask with DateOffset for Custom Frequencies

CustomBusinessHour can be combined with the DateOffset to create custom frequency aliases which consider both the custom business hour range and the weekmask for advanced time series manipulation.

Here’s an example:

from pandas.tseries.offsets import DateOffset

# Custom offset that adds business days considering the weekmask
custom_offset = cbh + DateOffset(days=1)



<CustomBusinessHour: CBH=09:00-17:00, weekmask='Mon Tue Wed Thu Fri'>

The example demonstrates how to combine a CustomBusinessHour object with a day offset to construct a custom frequency that respects the weekmask. It’s useful for performing time series shifts and resampling operations that align with specific business calendars.

Method 4: Integrating Weekmask with Holiday Calendar

Another advanced use for weekmask is integrating it with a holiday calendar to ensure both regular non-business days and specific holidays are excluded when calculating business hours. CustomBusinessHour accepts a ‘holidays’ parameter that can be used in conjunction with the weekmask.

Here’s an example:

from pandas.tseries.holiday import USFederalHolidayCalendar

cbh_with_holidays = CustomBusinessHour(start='09:00', end='17:00', 
                                       weekmask='Mon Tue Wed Thu Fri', 



DatetimeIndex([...], dtype='datetime64[ns]', freq=None)

This snippet creates CustomBusinessHour which considers the standard US federal holidays along with the regular Monday to Friday workweek. This setup is particularly useful when dealing with financial data where both weekends and public holidays need to be excluded from business hour computations.

Bonus One-Liner Method 5: Employing a Weekmask with a Custom Frequency String

If you prefer a succinct one-liner approach, you can define the weekmask directly in the string passed to frequencies like ‘CBH’ or ‘B’. This one-liner method is especially handy for quick manipulations.

Here’s an example:

resampled_data = data.resample('CBH', loffset='09:00', weekmask='Mon Wed Fri').mean()

The ‘resample’ method is adjusting the time series data according to the CustomBusinessHour frequency, offsetting the time by the start of the business hour, and only considering Monday, Wednesday, and Friday for the operation.


  • Method 1: Direct Initialization. Enables precise control during object creation. Can be restrictive if dynamic changes are required later.
  • Method 2: Dynamic Modification. Allows flexibility to update the weekmask. Might cause inconsistency if changed frequently in a shared environment.
  • Method 3: Weekmask with DateOffset. Suited for custom frequency creation. Requires a good understanding of pandas offset aliases.
  • Method 4: Integration with Holiday Calendar. Ideal for comprehensive business hour calculations. The complexity increases with additional holiday rules.
  • Method 5: One-liner Frequency String. Quick and straightforward for basic needs. Lacks the explicit clarity of object-oriented methods.