Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks By Jonathan Schwabish
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- 464
- File size
- 9.14 MB
- Format
- Digital PDF
- Course
- Education
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- eBook[PDF]
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About this ebook
Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks by Jonathan Schwabish is an essential manual designed to help data creators move beyond basic bar, line, and pie charts. The book features more than 500 examples and outlines a comprehensive toolkit divided into three core sections: [1, 2, 3]
1. Principles of Data Visualization
- Formulating Your Message: How to clearly define your target audience, identify core communication goals, and match your data to the right graphic. [1, 2]
- Visual Perception & Ethics: The core do’s and don’ts of chart design, how humans process visual information, and how to use data responsibly and ethically without misleading the viewer. [1, 2]
- Design Strategy: The rationale behind starting visual layouts in gray to intentionally direct audience focus before selectively applying color. [1]
2. Survey of Chart Types
This core section functions as an encyclopedia of over 80 different visualization types, systematically organized by the specific data scenario or communication problem they solve. Major categories include: [1, 2, 3]
- Comparing Categories: Traditional frameworks and variations like bullet charts and waterfall charts.
- Time Series Data: Methods for tracking changes over time, including slope charts, area charts, sparklines, and bump charts.
- Data Distribution: Deeper statistical breakdowns featuring histograms, horizon charts, and ridgeline plots.
- Geospatial & Maps: Standard geographic charting along with specialized visualizations like choropleth maps.
- Relationships & Composition: Highlighting connections between variables and part-to-whole relationships.
- Qualitative Information: Guidance on visualizing non-numerical data and implementing effective, clean table designs. [1, 2, 3, 4, 5]
3. Designing and Redesigning Your Visual
- Style Guides: A practical framework for building a cohesive data visualization style guide to establish team or organizational consistency. [1]
- The Redesign Process: Real-world case studies showcasing visual overhauls, taking ineffective charts (such as distorted 3D graphics) and breaking down the practical steps to restructure them for maximum clarity. [1, 2]
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