5 Free Tutorials to Master Data Visualization with Seaborn
Data visualization in Python is a piece of cake with seaborn. Learn one of the most popular Python data visualization libraries with these five free tutorials.
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If you want to easily create funky visualizations in Python, you should learn Seaborn. It’s one of the Python data visualization libraries the Python community can’t live without for the reasons listed in the image below.
It’s a library built on top of Matplotlib. While using seaborn doesn’t require knowledge of matplotlib, knowing both allows you to leverage the advantages of both libraries simultaneously. As a Matplotlib user, you’ll benefit from seaborn’s ease of use, better-looking plots, and specialization in statistical plots.
So, how do you learn making visualizations in such a cool library, except by going through seaborn’s very educational documentation? Which I strongly advise you to use, along with these five free tutorials.
1.Python Seaborn Tutorial For Beginners: Start Visualizing Data – DataCamp
Level: Beginner
Link: Python Seaborn Tutorial For Beginners: Start Visualizing Data
Description: This beginner-friendly tutorial introduces you to seaborn basics, which include:
- Seaborn description and comparison with matplotlib
- Installation guide
- Introduction to built-in datasets for demonstrating different seaborn features
- Commonly used seaborn plots and code examples of how to create them
- Plots customization
- Best practices
- Comparison with other visualization libraries
2.Intro to Seaborn – Youtube
Level: Beginner
Link: Intro to Seaborn
Description: This YouTube playlist is created for seaborn beginners who prefer learning by watching videos. It consists of 26 videos, with 24 videos explaining one common seaborn plot each.
3.The Ultimate Python Seaborn Tutorial: Gotta Catch ‘Em All – Elite Data Science
Level: Beginner
Link: The Ultimate Python Seaborn Tutorial: Gotta Catch ‘Em All
Description: This is a tutorial designed for those who want to use seaborn for data exploration and presentation. It covers topics similar to the previous tutorial but more succinctly.
4. Python Seaborn Tutorial – GeeksforGeeks
Level: Beginner to Intermediate
Link: Python Seaborn Tutorial
Description: This tutorial takes a similar approach to the previous one, only it delves deeper into more advanced plot creation. Along with more relational, categorical, and distribution plots than in the previous tutorial, you’ll also learn about creating regression plots.
5. Visualizing Data in Python With Seaborn – Real Python
Level: Intermediate
Link: Visualizing Data in Python With Seaborn
Description: This tutorial is for those who already have some experience with Python and data visualizations. Again, the topics covered are similar to the previous tutorials, only in more technical and theoretical depth.
You will learn about:
- Axis- and figure-level functions
- seaborn’s Contemporary Objects Interface
- Plot creation using functions
- Plot creation using objects
Bonus: Practicing Data Visualization in Seaborn
Once you get the basics of seaborn, you should practice it in real-world case scenarios so the skill really sinks in.
Here are several recommendations for practice resources:
- StrataScratch: Real data visualization interview questions (also for matplotlib)
- seaborn-data: A GitHub repository with datasets for seaborn
- Kaggle: A go-to source for a plethora of free real datasets.
- Google Cloud Public Datasets: Public datasets on Google Cloud.
- Data.gov: The US Government’s datasets.
- UCI Machine Learning Repository: A University of California Irvine’s data repository you can filter by data types, attributes, subject area, task, etc.
Conclusion
Whether you’re a Python data visualization beginner or a seasoned matplotlib user, seaborn is there to make your life easier. In just a few lines of code, you can produce publication-ready and easily customizable visualizations.
The above five free courses will ease you into the specifics of data visualization with seaborn.
Nate Rosidi is a data scientist and in product strategy. He's also an adjunct professor teaching analytics, and is the founder of StrataScratch, a platform helping data scientists prepare for their interviews with real interview questions from top companies. Nate writes on the latest trends in the career market, gives interview advice, shares data science projects, and covers everything SQL.