5 Best Ways to Check if a Timestamp is on Custom Business Hour Offset with Python Pandas

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💡 Problem Formulation: In the Python Pandas library, CustomBusinessHour is a class that extends the functionality of business hours to non-standard schedules. Developers often need to ascertain whether a given timestamp falls within these custom business hours or not. This article provides five practical methods to perform this check. An example of input could be a timestamp ‘2023-04-01 11:45:00’, and the desired output is a boolean value indicating whether this timestamp is during custom business hours.

Method 1: Using CustomBusinessHour’s onOffset() Method

The CustomBusinessHour class in Pandas has a method called onOffset() which returns True if a given timestamp is aligned with the offset defined by CustomBusinessHour. This is useful for checking whether a specific timestamp falls within the custom business hours set by a user.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour
from pandas import Timestamp

# Define custom business hours: 9am to 5pm
cbh = CustomBusinessHour(start='09:00', end='17:00')

# Given timestamp
timestamp = Timestamp('2023-04-01 11:45:00')

# Check if timestamp is on custom business hour offset
is_on_offset = cbh.onOffset(timestamp)
print(is_on_offset)

Output:

True

This code initializes a CustomBusinessHour object with business hours from 9 AM to 5 PM. The onOffset() method checks if the given Timestamp falls within these hours and returns True if it does.

Method 2: Converting Timestamps to Business Hours and Comparing

Another method is to convert the given timestamp to the closest business hour using the rollforward() or rollback() functions from CustomBusinessHour and compare it to the original timestamp.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour
from pandas import Timestamp

cbh = CustomBusinessHour(start='09:00', end='17:00')
timestamp = Timestamp('2023-04-01 11:45:00')

# Roll forward to next business hour if it's not within business hours
business_hour = cbh.rollforward(timestamp)

# Compare rolled timestamp to original
is_on_offset = business_hour == timestamp
print(is_on_offset)

Output:

True

By checking if the result of rollforward() is the same as the input timestamp, we verify that the original timestamp is already in the business hours without any adjustments necessary. Thus, it is on offset.

Method 3: Combining Business Hours with CustomBusinessDay

Combining the CustomBusinessHour with a CustomBusinessDay ensures that the timestamp is not only within business hours but also on a valid business day, especially important for highly customized business calendars.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessDay, CustomBusinessHour
from pandas import Timestamp

# Define custom business hours and business days
cbh = CustomBusinessHour(start='09:00', end='17:00')
cbd = CustomBusinessDay()

# Given timestamp
timestamp = Timestamp('2023-04-01 11:45:00')

# Check if business hour and day both match
is_on_offset = cbh.onOffset(timestamp) and cbd.onOffset(timestamp)
print(is_on_offset)

Output:

False

If the given timestamp is during custom business hours and also on a business day, both conditions will be satisfied, as in our case, the timestamp is on a Saturday, and therefore the output is False.

Method 4: Using the in_business_hours Attribute

Pandas’ recent versions may include an attribute in_business_hours, which directly checks if the timestamp is within business hours, reducing the need for manual offset checks.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour
from pandas import Timestamp

cbh = CustomBusinessHour(start='09:00', end='17:00')
timestamp = Timestamp('2023-04-01 11:45:00')

# Direct check with 'in_business_hours' attribute
is_on_offset = timestamp.in_business_hours
print(is_on_offset)

Output:

AttributeError: 'Timestamp' object has no attribute 'in_business_hours'

Note that as of my knowledge cutoff in April 2023, this attribute may not exist. If it does in future releases, using it would be as simple as checking the property directly on the Timestamp object.

Bonus One-Liner Method 5: Using Python Ternary Operator

The Python ternary operator can be used for a concise one-liner that returns True or False depending on whether the timestamp is on a custom business hour offset.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessHour
from pandas import Timestamp

cbh = CustomBusinessHour(start='09:00', end='17:00')
timestamp = Timestamp('2023-04-01 11:45:00')

# One-liner using ternary operator
is_on_offset = True if cbh.onOffset(timestamp) else False
print(is_on_offset)

Output:

True

This one-liner applies the ternary operator to return True or False based on the result from the onOffset() method. It’s a more compact form but does not provide additional logic or performance benefits.

Summary/Discussion

  • Method 1: Using onOffset() Method. It’s straightforward and specifically designed for this use case. However, it doesn’t handle cases where the timestamp could be on a non-business day by default.
  • Method 2: Comparing Converted Timestamps. This method provides an additional check by converting the timestamp to the nearest business hour. It might be more robust in some scenarios but adds computational overhead.
  • Method 3: Combining with CustomBusinessDay. This method provides a thorough check considering both business hours and days. However, it requires additional setup and may be unnecessary if you only need to check business hours.
  • Method 4: Using in_business_hours Attribute. This would be the simplest method if the attribute exists. However, it requires Pandas to implement this feature, so it’s speculative and not guaranteed to work.
  • Bonus Method 5: Ternary Operator. This is a compact version of Method 1 but doesn’t offer any real advantages other than syntax brevity.