References

Books

• C. O. Wilke Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures (O’Reilly Media, 2019), https://books.google.com/books?id=XmmNDwAAQBAJ.

  • This book is intentionally technology agnostic, but (nearly) all of the figures were generated using ggplot2 in R. You can find the source code for book on the campanion github site.

• K. Healy Data Visualization: A Practical Introduction (Princeton University Press, 2019), https://books.google.com/books?id=3XOYDwAAQBAJ.

  • This is primarily a book about creating graphics with ggplot2 in R, but the opening chapter discusses general principles for designing good graphics. These are then illustrated using ggplot2 in the remaining chapters.

• N. Yau Visualize This: The FlowingData Guide to Design, Visualization, and Statistics (Wiley, 2011), https://books.google.com/books?id=CB9XRIv9oigC.

  • Available as e-book through the Hekman Library.

• C. N. Knaflic Storytelling with Data: A Data Visualization Guide for Business Professionals (Wiley, 2015), https://books.google.com/books?id=IheRCgAAQBAJ.

• C. N. Knaflic Storytelling with Data: Let’s Practice! (Wiley, 2020), https://github.com/Saurav6789/Books-/blob/master/Storytelling%20with%20Data%20Let%E2%80%99s%20Practice%20by%20Cole%20Nussbaumer%20Knaflic%20(z-lib.org).pdf.

  • data, solutions, etc.

Articles

• JooYoung Seo and Mine Dogucu “Teaching Visual Accessibility in Introductory Data Science Classes with Multi-Modal Data Representations,” Journal of Data Science 21, no. 2 (2023): 428–41, https://doi.org/10.6339/23-JDS1095.

Visualization Galleries

• R Graph Gallery

• Vega-Lite Example Gallery

• Altair Example Gallery

Blog sites and posts

• Data Underload by Nathan Yau

• Five charts you’ve never used, but should by Jonathan Schwabisch

Data Sources

Software Related

Vega-Lite (and Altair)

• The Vega editor – create graphics online

• The Visulization Curriculum developed at the University of Washington by Jeffrey Heer, Dominik Moritz, Jake VanderPlas, and Brock Craft.

• Jonathan Zong et al. “Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics,” IEEE Transactions on Visualization and Computer Graphics 29, no. 1 (2023): 149–59, https://doi.org/10.1109/TVCG.2022.3209369.

• Jacob VanderPlas et al. “Altair: Interactive Statistical Visualizations for Python,” Journal of Open Source Software 3, no. 32 (2018): 1057, https://doi.org/10.21105/joss.01057.

• Vega-Lite Example Gallery

Plotly

• C. Sievert Interactive Web-Based Data Visualization with r, Plotly, and Shiny, Chapman & Hall/CRC the r Series (CRC Press, 2020), https://books.google.com/books?id=7zPNDwAAQBAJ.

ggplot2

• H. Wickham Ggplot2: Elegant Graphics for Data Analysis, Use r! (Springer International Publishing, 2016), https://books.google.com/books?id=RTMFswEACAAJ.

• ggplot2 extensions gallery

  • Many add-on packages have been created to add additional features or plots that handle specific situations.

Additional References

• Edward R. Tufte The Visual Display of Quantitative Information, 2nd ed. (Cheshire, CT: Graphics Press, 2001).