How To Make Grouped Boxplot with Seaborn Catplot? Last Updated : 23 Jul, 2025 Comments Improve Suggest changes Like Article Like Report Prerequisite: seaborn A grouped boxplot is a boxplot where categories are organized in groups and subgroups. Whenever we want to visualize data in the group and subgroup format the Seaborn Catplot() plays a major role. The following example visualizes the distribution of 7 groups (called A to G) and 2 subgroups (called low and high) in grouped boxplot format. To generate boxplot using Seaborn generally uses the boxplot() method but here we use a much newer method Catplot(). The Catplot() accesses several axes-level functions that show the relationship between a numerical and one or more categorical variables using one of several visual representations. Grouped Boxplot In this article, we will learn how to generates Grouped Boxplot using Seaborn Catplot. Please follow the steps mentioned below - Import required packages.Load the dataset.Now use catplot() method which is available within the seaborn package. Let's pass the x and y variable, here the variable on the x-axis is continuous and the variable on the y-axis is categorical also pass other parameters like data, hue, height, aspect, and kind=" box". Syntax: catplot(x, y, hue, data, height ,kind) Example 1: Horizontal Boxplot Python3 import pandas as pd import seaborn as sns df = pd.read_csv("titanic_train.csv") df.dropna() sns.catplot(x='Sex', y='Fare', hue='Survived', data=df, height=9, kind="box") Output : Example 2: Vertical Boxplot This example depicts how we can plot the same data horizontally. This can be achieved simply by swapping values provided to x and y. Python3 import pandas as pd import seaborn as sns df = pd.read_csv("titanic_train.csv") df.dropna() sns.catplot(y='Sex', x='Fare', hue='Survived', data=df, height=9, kind="box") Output: Comment More infoAdvertise with us A abhijitmahajan772 Follow Improve Article Tags : Python Python-Seaborn Practice Tags : python Explore Python FundamentalsPython Introduction 3 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 5 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 7 min read Python Functions 8 min read Recursion in Python 6 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 5 min read Python Tuples 4 min read Dictionaries in Python 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 10 min read Python Exception Handling 6 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 2 min read Python MySQL 9 min read Python Packages 12 min read Python Modules 7 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 11 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 6 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 15+ min read StatsModel Library- Tutorial 4 min read Learning Model Building in Scikit-learn 8 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 7 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 10 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 7 min read Python | Build a REST API using Flask 3 min read How to Create a basic API using Django Rest Framework ? 4 min read Python PracticePython Quiz 3 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like