ggplot in Python allows you to build data visualizations in a very concise and consistent way. As you’ve seen, even complex and beautiful plots can be made with a few lines of code using plotnine.
In this course, you’ve learned how to:
- Install plotnine and Jupyter Notebook
- Combine the different elements of the grammar of graphics
- Use plotnine to create visualizations in an efficient and consistent way
- Export your data visualizations to files
If you want to learn more about grammars of graphics, you can check out the following resources on the topic:
Leland Wilkinson’s book is a standard lecture on this topic. Hadley Wickham’s paper, which you can read as a free PDF online, describes the basics for the implementation of a grammar of graphics in the R library ggplot2 that serves as the base for Python’s
If you want to learn more about building data visualizations in Python and the underlying libraries that
plotnine relies on, then you can check out:
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.