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)
Dataset used: titanic_train.csv
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:
