Visualizing Data

by William S. Cleveland
Visualizing Data cover
Good Books rating 4.17
Science and Innovation
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Format • £30.39
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Technical
  • ID: 2084
  • Added: 2025-10-11
  • Updated: 2025-10-12
  • Publisher: Hobart Press
  • Published: 1993-01-01
  • Formats: 6
  • Reviews: 3

Visualizing Data is a comprehensive guide to the art and science of data visualization. It explores the principles and techniques that make data more accessible and understandable. The book delves into the psychology of perception, the importance of storytelling with data, and the tools and technologies that can help you create effective visualizations. Whether you're a data scientist, a business analyst, or simply someone who wants to make better sense of the world, this book will equip you with the skills to turn raw data into meaningful insights. From static charts to interactive dashboards, Visualizing Data covers a wide range of visualization types and their applications. It also provides practical advice on how to choose the right visualization for your data and audience, ensuring that your message is clear and impactful. With real-world examples and case studies, this book is an essential resource for anyone looking to harness the power of data visualization.

Reviews
Reddit · 2025-10-11
good 4.00

The book is recommended for its comprehensive overview of data visualization techniques, making it a go-to resource for those seeking to understand and apply these methods.

In a Reddit discussion, users highlight Visualizing Data as a top recommendation for understanding data visualization. They appreciate the book's thorough coverage of various techniques and its practical applications. The community finds it particularly useful for those looking to gain a solid foundation in data visualization. The consensus is that this book is an essential read for anyone interested in the field.

Quick quotes

    Edward Tufte - The Visual Display Of Quantitative Information

    If you just want a solid foundation in data visualization, this book is a great starting point.

    The book is highly recommended for its comprehensive overview and practical applications.

ProQuest · AM Ellison · 2025-10-11
great 4.00

The reviewer finds coplots and scatterplot matrices particularly effective for higher-order data, praising the book's methods for their clarity and utility.

AM Ellison's review emphasizes the effectiveness of coplots and scatterplot matrices in handling higher-order data. They appreciate how these methods, when combined with other techniques, provide deep insights into data structure. Ellison highlights the book's practical applications and its ability to make complex data more accessible and understandable. The reviewer's overall impression is that this book is a valuable tool for anyone working with data visualization.

Quick quotes

    Cleveland shows that coplots and scatterplot matrices are excellent methods to work with higher-order data.

    Especially when combined with the techniques described, these methods provide deep insight into the structure of data.

    A valuable tool for anyone working with data visualization.

TandFOnline · Lloyd S. Nelson · 2025-10-11
excellent 4.50

The book is praised for its rigorous approach to data visualization, making it a valuable resource for those interested in statistical graphing. The reviewer appreciates the depth and practicality of the techniques presented.

Lloyd S. Nelson highlights that this book is a must-read for anyone serious about data visualization. They commend Cleveland's pioneering work and the book's comprehensive coverage of statistical graphing techniques. Nelson notes that the book goes beyond basic charts and graphs, offering insights into designing interfaces for complex data sets. The practical applications and rigorous scientific approach make it a standout resource in the field.

Quick quotes

    This book is a must-read for anyone serious about data visualization.

    Cleveland's pioneering work in statistical graphing is thoroughly covered.

    The book offers insights into designing interfaces for complex data sets.

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