Understanding Python Pandas Frequency Names in BusinessDay Offset Objects

💡 Problem Formulation: When using pandas in Python for data analysis, it’s common to work with date offsets, especially when dealing with business dates. However, it’s not always straightforward to determine the name of the frequency applied on a given BusinessDay offset object. This article walks you through various methods to retrieve the frequency name, demonstrating each with clear examples and explaining the output for a better understanding.

Method 1: Accessing the `name` Attribute

An effective and direct approach to find out the frequency name of a BusinessDay object is to access its name attribute. This property holds the name of the frequency as a string.

Here’s an example:

from pandas.tseries.offsets import BusinessDay

bday = BusinessDay()
print(bday.name)

Output:

'B'

This code snippet first imports the BusinessDay class from the pandas library. It then creates an instance of a BusinessDay and prints out the name of the frequency by accessing the name attribute of the object, which, in this case, is ‘B’ for business day.

Method 2: Using the `freqstr` Attribute

If you are working with a time series index that has a business day frequency, you can obtain the frequency name by checking the freqstr attribute attached to the index.

Here’s an example:

import pandas as pd

date_range = pd.date_range(start="2021-01-01", periods=5, freq='B')
print(date_range.freqstr)

Output:

'B'

This code utilizes pandas.date_range to create a range of dates with a business day frequency. The resulting dates are stored in date_range, which has a freqstr attribute. The attribute reveals the string code for the frequency, which is ‘B’ for business days.

Method 3: Calling `resolution_string()` Function

For more complex frequency setups, you can use the resolution_string() function available in pandas to get a human-readable frequency description.

Here’s an example:

from pandas.tseries.frequencies import to_offset

offset = to_offset('2B')
print(offset.resolution_string())

Output:

'business day'

Here, to_offset('2B') creates a business day offset for a frequency of two business days. The resolution_string() method then returns a descriptive name of the frequency. In this example, ‘business day’ is outputted, indicating the type of frequency applied.

Method 4: Inspecting the `rule_code` Property

Another way to determine the frequency name is by inspecting the rule_code property of the DateOffset object.

Here’s an example:

from pandas.tseries.offsets import BDay

frequency = BDay()
print(frequency.rule_code)

Output:

'B'

In this snippet, BDay() is an alias for BusinessDay(), used to create a business day frequency object. frequency.rule_code returns the shorthand rule code for the frequency, which is ‘B’.

Bonus One-Liner Method 5: Using `repr()`

You can also get the frequency name by converting the BusinessDay object to its string representation using the built-in repr() function.

Here’s an example:

from pandas.tseries.offsets import BusinessDay

bday = BusinessDay()
print(repr(bday))

Output:

'<BusinessDay>'

Utilizing repr(bday) on a BusinessDay object provides the string representation of the object itself, which includes the type of offset object in angle brackets.

Summary/Discussion

Method 1: Accessing name Attribute. Straightforward and simple. Limited to cases where the attribute is directly available on the offset object.
Method 2: Using freqstr Attribute. Ideal for data series with an index already set. Depends on the presence of the attribute in the index object.
Method 3: Calling resolution_string(). Provides a more verbose description. May not provide the abbreviation and is more complex than other methods.
Method 4: Inspecting rule_code. Gives the rule code directly associated with the frequency. Might not be as descriptive as the actual name.
Bonus Method 5: Using repr(). A quick one-liner providing the object’s string representation. Does not give a concise frequency abbreviation but shows the type of offset.