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Advanced pandas—Going Beyond the Basics

GroupBy—Further Useful Features

Explore advanced features of the pandas GroupBy method to enhance your data reshaping and analysis skills. Learn to select, iterate, and filter groups, handle numeric-only calculations, extract specific rows, and apply the Grouper class for time-based grouping. This lesson helps you manage complex data scenarios effectively.

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Overview of further useful features

Having covered the standard functions across the three categories—aggregate, transform, and filter—let’s explore the other valuable features associated with the groupby() method. Although these features are less well-known, they can certainly be helpful in numerous use cases and scenarios.

Group selection

We can use the get_group() method on the GroupBy object to return rows belonging to a specific group. For example, if we would like to obtain the data for customers who are students (i.e., rows with the Yes value in the Student column).

Python 3.10.4
# Generate GroupBy object

grouped = df.groupby('Student')



# Retrieve the student group (i.e., Yes value in Student column)

student_group = grouped.get_group(name='Yes')



print(student_group)

We can also use get_group() on GroupBy objects grouped on multiple columns. For example, if we want to retrieve the group of customers who are students and aren’t married.

Python 3.10.4
# Generate GroupBy object

grouped = df.groupby(['Student', 'Married'])



# Retrieve single students (i.e., Student Yes, Married No)

single_student_group = grouped.get_group(name=('Yes', 'No'))



print(single_student_group)

If we want to filter the output of the GroupBy object to specific columns (e.g., Income and Balance), we can subset it with the standard square brackets.

Python 3.10.4
# Generate GroupBy object

grouped = df.groupby(['Student', 'Married'])[['Student', 'Married', 'Income', 'Balance']]



# Retrieve single students (i.e., Student Yes, Married No)

single_student_group = grouped.get_group(name=('Yes', 'No'))



print(single_student_group)

Iterate through groups

A GroupBy object is a Python generator that we can iterate with. The generator yields a sequence that returns a pair of objects at each iteration—the group name and the subset DataFrame of each group. For example, we can iterate over a GroupBy object that is grouped based on Ethnicity to obtain the name of the ...