The Best Data Visualization Books

Data Visualization in Excel: A Guide for Beginners, Intermediates, and Wonks by Jonathan Schwabish: This is a guidebook that helps users to create advanced and persuasive data visualizations in Excel, written to bridge the gap between what people think Excel can do and what it can actually achieve in terms of data visualization. It's a step-by-step guide for anyone who wants to create better, more effective and more engaging visual displays. It's ideal for individuals in the business world, where Excel is ubiquitous, and who want to expand its capabilities beyond its default chart options.

Interactive Visual Data Analysis by Christian Tominski and Heidrun Schumann: This book is accessible to a broad interdisciplinary audience, from students to experts in the field to practitioners in data-intensive application domains. That's because it advocates for the synthesis of visualization, interaction and automatic computation to facilitate insight generation and knowledge crystallization from complex big data sets. This book also discusses data analysis and techniques to practice interactive visualization.

Making with Data: Physical Design and Craft in a Data-Driven World edited by Samuel Huron, Till Nagel, Lora Oehlber and Wesley Willett: This book provides an in-depth exploration of the diverse practices used by contemporary creators to produce objects, spaces and experiences infused with data. The book features over 25 beautifully illustrated chapters, where international artists, designers and scientists explain the process of creating data-driven functional art and illustrate their practice with candid sketches, photographs and design artifacts from their own studios.

Mobile Data Visualization edited by Bongshin Lee, Raimund Dachselt, Petra Isenberg and Eun Kyoung Choe: This book is the first to provide an overview of how to effectively visualize, analyze and communicate data on mobile devices. The authors were able to achieve this by drawing from the expertise, research and experience of an international range of academics and practitioners from several relevant data and computer science fields, such as ubiquitous computing and human-computer interaction.

Questions in Dataviz: A Design-Driven Process for Data Visualisation by Neil Richards: This three-part book takes readers through a unique journey of learning and creating data visualizations by posing key questions every step of the way. It encourages readers to think creatively and challenge best practices by providing beautiful visualization examples and key discussion points — as well as covering fundamental principles useful for presenting data visualization projects. It's especially helpful for those at a beginner or intermediate level seeking inspiration and alternative ways to apply their data visualization skills. View an interview with the author here. 

Visualization Analysis and Design by Tamara Munzner: This book covers a range of visualization techniques, including information visualization, scientific visualization and visual analytics. It emphasizes on validation of effectiveness and function before form. The book is structured around three key questions of visualization design: what, why and how. Moreover, it can be used as a textbook for a practical introduction into a visualization course at the graduate or undergraduate level.

Visualizing with Text by Richard Brath: Useful for designers, developers and academics, this is a comprehensive guide that covers the use of text elements in visualizations from simple labels to full documents. It builds a robust foundation for the design space of text in visual information using a multidisciplinary research effort and introduces new visualization techniques that use text. It bridges the gap between visualization, typography, text analytics and natural language processing.

Data-Driven Storytelling edited by Nathalie Henry Riche, Christophe Hurter, Nicholas Diakopoulos and Sheelagh Carpendale: This book is a result of a collaboration between data visualization researchers and data journalists and offers an in-depth definition of the topic, providing examples of functional art and patterns for data storytelling — as well as highlighting key challenges and opportunities for researchers and practitioners in the field.

Information Theory Tools for Visualization by Min Chen, Miquel Feixas, Ivan Viola, Anton Bardera, Han-Wei Shen and Mateu Sbert: Written by experienced academics, this book provides a comprehensive and current look at the information theory (IT) tools currently available for data visualization. The book covers the most recent developments and trends in information theory and visualization and is the first resource of its kind solely dedicated to this subject — which has made it popular among professionals dedicated to computer science.