Better Data Visualizations

Better Data Visualizations

A Guide for Scholars, Researchers, and Wonks

  • Author: Schwabish, Jonathan
  • Publisher: Columbia University Press
  • ISBN: 9780231193108
  • eISBN Pdf: 9780231550154
  • Place of publication:  New York , United States
  • Year of digital publication: 2021
  • Month: February
  • Language: English
Now more than ever, content must be visual if it is to travel far. Readers everywhere are overwhelmed with a flow of data, news, and text. Visuals can cut through the noise and make it easier for readers to recognize and recall information. Yet many researchers were never taught how to present their work visually.

This book details essential strategies to create more effective data visualizations. Jonathan Schwabish walks readers through the steps of creating better graphs and how to move beyond simple line, bar, and pie charts. Through more than five hundred examples, he demonstrates the do’s and don’ts of data visualization, the principles of visual perception, and how to make subjective style decisions around a chart’s design. Schwabish surveys more than eighty visualization types, from histograms to horizon charts, ridgeline plots to choropleth maps, and explains how each has its place in the visual toolkit. It might seem intimidating, but everyone can learn how to create compelling, effective data visualizations. This book will guide you as you define your audience and goals, choose the graph that best fits for your data, and clearly communicate your message.
  • Table of Contents
  • Introduction
  • Part I: Principles of Data Visualization
    • 1. Visual Processing and Perceptual Rankings
    • 2. Five Guidelines for Better Data Visualizations
    • 3. Form and Function
  • Part II: Chart Types
    • 4. Comparing Categories
    • 5. Time
    • 6. Distribution
    • 7. Geospatial
    • 8. Relationship
    • 9. Part-to-Whole
    • 10. Qualitative
    • 11. Tables
  • Part III: Designing and Redesigning Your Visual
    • 12. Developing a Data Visualization Style Guide
    • 13. Redesigns
  • Conclusion
  • Appendix 1. Data Visualization Tools
  • Appendix 2. Further Reading and Resources
  • Acknowledgments
  • References
  • Index


By subscribing, you accept our Privacy Policy