# Sunburst Plot using Python

Sunburst plot is an amazing visualization technique used to visualize hierarchical data. It extends radially outward from the root to the leaves to visualize hierarchical data. If you’ve never used sunburst charts before to visualize your dataset, this article is for you. In this article, I’ll show you a tutorial on how to visualize a sunburst plot using Python.

## Sunburst Plots

A sunburst plot is a very popular data visualization technique used to visualize hierarchical data where each level of the hierarchy is represented by a ring or circle where the innermost circle or ring is the highest level of the hierarchy. Sunburst charts are best to be used when analyzing a dataset where the output of a variable can be split into multiple factors.

You can visualize a sunburst plot with any data visualization tool like Tableau, Microsoft Excel, or Python libraries like Plotly. So in the section below, I will take you through a quick tutorial on how to visualize a sunburst plot using the plotly library in Python.

## Sunburst Plot using Python

To visualize sunburst plots, I’ll be using the plotly library in Python. So if you’ve never used it before, you can easily install it on your system using the pip command:

• pip install plotly

Now here is how you can visualize a sunburst plot using Python:

### Summary

So this is how you can easily visualize sunburst plots using Python. Always remember to only use sunburst plots on a hierarchical dataset, otherwise, it will look like a donut plot. A sunburst plot is a very popular data visualization technique used to visualize hierarchical data where each level of the hierarchy is represented by a ring or circle where the innermost circle or ring is the highest level in the hierarchy. Hope you liked this article on how to visualize sunburst plots using Python. Please feel free to ask your valuable questions in the comments section below. ##### Aman Kharwal

I'm a writer and data scientist on a mission to educate others about the incredible power of data📈.

Articles: 1534