Introduction to matplotlib

This chapter provides an introduction to matplotlib workflows for visualizing data in Python.

Acknowledgements

The author consulted the following materials when building this tutorial:

• matplotlib, “Usage Guide”

• matplotlib, “Tutorials”

• pandas documentation, “Getting Started: Plotting”

• Chapter 9 “Plotting and Visualization” from Wes McKinney, Python for Data Analysis: Data Wrangling With pandas, Numpy, and IPython (O’Reilly, 2017)

• Ventsislav Yordanov, “Data Science with Python: Intro to Data Visualization with Matplotlib” Towards Data Science (21 July 2018)

• Chapter 15 “Generating Data” from Eric Matthes, Python Crash Course: A Hands-On, Project-Based Introduction to Programming (No Starch Press, 2019).

• Chapter 4 “Visualization with Matplotlib” from Jake VanderPlas, Python Data Science Handbook: Essential Tools for Working with Data (O’Reilly, 2016)

All figures in this lab come from the matplotlib documentation and tutorials.

Chapter Contents

• Introduction to Matplotlib
• Matplotlib Basics
• Customizing in Matplotlib
• Other Plot Types
  • Scatterplots
  • Histograms
  • Additional Resources
  • Bar Charts
  • Pie Charts
  • Box Plots
  • Subplots
• Saving & Exporting
• Additional Resources
• Application

Application

Click here for a Jupyter Notebook template for this chapter’s application problems.