Plotting Categorical Data with Seaborn in Python

This tutorial will teach you how to plot categorical data in Python using the Seaborn library.

Before we begin, you must know what the seaborn library is all about. You must also have the Seaborn library installed on your system.

Installing Seaborn

Seaborn is a data visualization library based on matplotlib and you can use it to create beautiful, detailed graphs using Python.

If you have seaborn already installed on your system, you can skip this step.

To install Seaborn, you can refer to the following page:-

Line chart plotting using Seaborn in Python

 

Importing the required libraries

First of all, we will import the required libraries before using them.

import seaborn as sns

The ‘as’ keyword creates an alias. So, whenever we want to use a function from seaborn, we can just use ‘sns’ instead.

 

What Is Categorical Data?

Categorical Data is nothing but data that has categories, as the name implies. For example, we can consider gender to be categorical data (male and female). Similarly, hair color, skin tone, etc are all examples of categorical data.

An important aspect of categorical data is that categorical data can be sorted in any way; the meaning of the data will remain the same. This means that there is no implicit ordering to categorical data and can be ordered in any random way.

 

Categorical Data can be plotted in many ways. In this tutorial, I will be showing you how to plot categorical data using bar plots as it is very commonly used.

 

Let’s get started!

We can plot categorical graphs in various different ways. In this tutorial, I will be using a dataset that represents the information about the people that were on the Titanic when it tragically sunk.

I will recommend you to download this dataset from the link below:-

titanic.csv

 

Python code: Plot Categorical Data with Seaborn in Python

#importing the libraries required 

import seaborn as sns


#Loading the dataset
dataset = sns.load_dataset('titanic')

#Plottint the bar plot
sns.barplot(x="sex",y="survived",data=dataset)

This code will create a bar plot that shows the number of females and males that survived in the Titanic tragedy.

The ‘sns.load_dataset’ function loads a dataset into a variable. The ‘sns.barplot()’ function plots the graph and shows the output.

The x value i.e., ‘sex’, in this case, is the set of values of the x-axis that are taken from the dataset. The y value i.e., ‘survived’, is the set of values of y-axis taken from the dataset.

 

OUTPUT:

Plot Categorical Data with Seaborn in Python

Also read:

Seaborn module of Python

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