Source code and course GitHub repository

github.com/talkpython/python-data-visualization

What's this course about and how is it different?

The python data visualization landscape has many different libraries. They are all powerful and useful but it can be confusing to determine what works best for you. This course is unique because you will learn about many of the most popular python visualization libraries. You will start by learning how to use each library to build simple visualizations. You will also explore more complex usage and identify the scenarios where each library shines.

By the end of this course, you will have a basic working knowledge of how to visualize data in python using multiple libraries. You will also learn which library is best for you and your coding style. Along the way, you'll learn general visualization concepts to make your plots more effective.

In addition to the overview material, we will cover some of the more complex, interactive visualization dashboard technologies.

What topics are covered

In this course, you will

Review the python visualization landscape

Explore core visualization concepts

Use matplotlib to build and customize visualizations

Build and customize simple plots with pandas

Learn about seaborn and use it for statistical visualizations

Create visualizations using Altair

Generate interactive plots using the Plotly library

Design interactive dashboards using Streamlit

Construct highly custom and flexible dashboards using Plotly's Dash framework

View the full course outline.

Who is this course for?

Developers and Data Analysts that have some experience with python but have not developed a competency in a python visualization library. This course is also helpful for those that feel restricted by their current plotting tools and wish to explore other options.

Note: All software used during this course, including editors, Python language, etc., are 100% free and open source. You won't have to buy anything to take the course.

Concepts backed by concise visuals

While exploring a topic interactively with demos and live code is very engaging, it can mean losing the forest for the trees. That's why when we hit a new topic, we stop and discuss it with concise and clear visuals.