Better Data Visualizations: A Guide For Scholars, Researchers, And Wonks

Description

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. Cover......Page 1 Title......Page 2 Title - complete......Page 4 Copyright......Page 5 Dedication......Page 6 Table of Contents......Page 8 Introduction......Page 16 Part I: Principles of Data Visualization......Page 26 1. Visual Processing and Perceptual Rankings......Page 28 2. Five Guidelines for Better Data Visualizations......Page 44 3. Form and Function......Page 68 Part II: Chart Types......Page 80 4. Comparing Categories......Page 82 5. Time......Page 148 6. Distribution......Page 194 7. Geospatial......Page 232 8. Relationship......Page 264 9. Part-to-Whole......Page 304 10. Qualitative......Page 326 11. Tables......Page 342 Part III: Designing and Redesigning Your Visual......Page 362 12. Developing a Data Visualization Style Guide......Page 364 13. Redesigns......Page 384 Conclusion......Page 406 Appendix 1. Data Visualization Tools......Page 412 Appendix 2. Further Reading and Resources......Page 418 Acknowledgments......Page 424 References......Page 428 Index......Page 446