Unlocking the Rule Code of CustomBusinessDay Objects in Pandas

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πŸ’‘ Problem Formulation: Python’s Pandas library is widely used for advanced data manipulation and analysis. A particular aspect of interest for financial analysts and data scientists is the ability to work with custom business day calendars using the CustomBusinessDay object. The challenge is to extract the specific rule code that was applied to create this object. For instance, if we define a CustomBusinessDay object to represent a business week excluding Wednesday, the desired output is to retrieve the rule code that indicates this custom business logic.

Method 1: Accessing the ‘weekmask’ Attribute

This method involves directly accessing the ‘weekmask’ attribute of a CustomBusinessDay object, which contains a string representing the days of the week that are considered business days.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessDay

# Define a CustomBusinessDay object
cbd = CustomBusinessDay(weekmask='Mon Tue Thu Fri')

# Access the 'weekmask' attribute
rule_code = cbd.weekmask
print("Rule Code:", rule_code)

Output:

Rule Code: Mon Tue Thu Fri

This code creates a CustomBusinessDay object that only considers Monday, Tuesday, Thursday, and Friday as valid business days. The weekmask attribute holds the rule code which is printed out, providing a straightforward approach to extract the day rules.

Method 2: Using the ‘holidays’ Attribute

Another way to obtain rule specifics is by accessing the ‘holidays’ attribute. This works well when the CustomBusinessDay object has been initialized with specific dates to exclude from the business week.

Here’s an example:

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

# Define a CustomBusinessDay object with specific holidays
cbd = CustomBusinessDay(holidays=[Timestamp('2023-01-01'), Timestamp('2023-12-25')])

# Access the 'holidays' attribute
rule_code = cbd.holidays
print("Rule Code:", rule_code)

Output:

Rule Code: DatetimeIndex(['2023-01-01', '2023-12-25'], dtype='datetime64[ns]', freq=None)

This snippet demonstrates how to initiate a CustomBusinessDay object with specific holiday dates. The holidays attribute then reveals these dates, allowing you to understand which specific instances have been designated as non-business days.

Method 3: Inspecting the ‘n’ Attribute for Offset Frequencies

For scenarios where the custom business day follows a certain frequency pattern, such as every other business day, the ‘n’ attribute of the CustomBusinessDay object will indicate this rule.

Here’s an example:

from pandas.tseries.offsets import CustomBusinessDay

# Define a CustomBusinessDay object with an offset frequency
cbd = CustomBusinessDay(n=2)

# Access the 'n' attribute
rule_code = cbd.n
print("Rule Code:", rule_code)

Output:

Rule Code: 2

In this example, the CustomBusinessDay object is initialized with an offset frequency of 2. This means that the rule code specifies an interval of every two business days, which is accessed through the n attribute.

Method 4: Crafting a Custom Function to Compile Rule Attributes

If multiple aspects determine the business day rules, such as the weekmask and holidays, one can write a custom function that compiles these into a single rule code.

Here’s an example:

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

def get_rule_code(cbd):
    rules = {
        'weekmask': cbd.weekmask,
        'holidays': cbd.holidays,
        'n': cbd.n
    }
    return rules

# Define a complex CustomBusinessDay object
cbd = CustomBusinessDay(weekmask='Mon Tue Thu Fri', holidays=[Timestamp('2023-01-01')], n=2)

# Invoke the custom function
rule_code = get_rule_code(cbd)
print("Rule Code:", rule_code)

Output:

Rule Code: {
    'weekmask': 'Mon Tue Thu Fri',
    'holidays': DatetimeIndex(['2023-01-01'], dtype='datetime64[ns]', freq=None),
    'n': 2
}

The custom function get_rule_code generates a dictionary consolidating the various components that define the CustomBusinessDay rule. In this example, the function captures the weekmask, holidays, and frequency offset, presenting a comprehensive view of the business day logic.

Bonus One-Liner Method 5: Exporting Object Properties to JSON

For a quick way to serialize the properties of a CustomBusinessDay object, including rule codes, into a JSON-compatible format, you may use Python’s built-in capabilities to convert object attributes to a dictionary and then to JSON.

Here’s an example:

import json
from pandas.tseries.offsets import CustomBusinessDay

# Define a CustomBusinessDay object
cbd = CustomBusinessDay()

# Export attributes to JSON
rule_code_json = json.dumps(cbd.__dict__)
print("Rule Code (JSON):", rule_code_json)

Output:

Rule Code (JSON): {"kwds": {}, "name": "C", "nano": 0, "normalize": false, "n": 1, ...}

This one-liner converts the properties of a CustomBusinessDay object to a JSON string. It is particularly useful for serialization and sharing of the rule settings, but might include additional attributes that are not part of the business logic definition.

Summary/Discussion

  • Method 1: Access ‘weekmask’. Straightforward and easy to implement. Only informative when the rule involves specific weekdays.
  • Method 2: Use ‘holidays’ attribute. Useful for rules with specific non-business days. Does not display weekday logic.
  • Method 3: Check ‘n’ attribute for frequency. Reveals interval-based business rules. Does not provide details on specific weekdays or holidays.
  • Method 4: Custom function to compile rules. Flexible and comprehensive. Requires extra code and maintenance.
  • Method 5: Export to JSON. Quick serialization of object attributes. May include unnecessary information.