Evolving Data Visualization: Crafting the Second Edition of Visualize This with Nathan Yau image
S10 E262 · The PolicyViz Podcast
Evolving Data Visualization: Crafting the Second Edition of Visualize This with Nathan Yau
887 Plays
24 days ago

Nathan Yau’s Flowing Data website was one of the first data visualization websites I discovered in my own data journey. With his new book, Visualize This, now out, I thought it would be a great opportunity to talk with Nathan about his work, his book, and how his own approach to data has evolved over the last several years.

The new edition of Visualize This enriches readers with modern techniques and examples, focusing on effectively learning data visualization by exploring different data types and designing for clear communication, even for those without a formal design background. Nathan emphasizes the necessity of audience-appropriate visualizations and the selection of suitable tools, all of which have changed and evolved since the first edition of the book was published in 2011.

We obviously talk about the latest book in this episode of the podcast, including Nathan’s process for creating graphics (a lot of R and Adobe Illustrator), his professional growth from a statistics PhD program to embracing full-time visualization work. We discuss the nuances of handling feedback, the differentiation between misinformation and subjective interpretation, and the significance of constructive criticism. We also touch on challenges for newcomers in the field, the need for clearer communication of uncertainty, and the potential of virtual and augmented reality.

➡️ Check out more links, notes, transcript, and more at the PolicyViz website.

Topics Discussed

  • Updated Techniques and Modern Examples: Nathan’s new edition of “Visualize This” brings to the forefront the latest in data visualization, incorporating modern techniques and examples that cater to both beginners and seasoned practitioners.
  • Learning by Exploring: The book emphasizes a hands-on approach to understanding data visualization. It guides readers through exploring different data types and designing visualizations that communicate clearly, irrespective of the reader’s design background.
  • Personal Data Collection and Analysis: Nathan shares his insights into the importance of personal data collection for self-analysis, a practice influenced by his time at the New York Times. This self-exploratory journey into data helps individuals understand the nuances of their own information.
  • The Growth of Flowing Data: Nathan reflects on the evolution of his      platform, Flowing Data, highlighting its expansion to include daily      emails, tutorials, and personal projects.
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