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- Thematic Mapping
Thematic Mapping
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Not all maps are made equally. Not all maps are read equally. Every map is a product of its maker, and its reader, and maps are rarely right or wrong but simply different versions of the truth. The meaning you see in a map can reinforce or challenge your understanding of the theme it represents, and you are much more likely to believe a map if it presents a version of the truth that you believe in already. But how do you decide what map you want to make? How do you understand the way in which different maps can be used in different ways to tell a story? How do you design a map to be read in a particular way? This book answers these questions, and more.
Using 101 maps, graphs, charts, and plots of the 2016 United States presidential election data this book explores the rich diversity of thematic mapping and the visual representation of data. It details well-known techniques and shows you how to design effective maps and graphics. It also shows innovative and fascinating alternative ways of making maps of data which you can use in your own work. Each map illustrates a different approach to the same data, and all lead to different maps and different ways of seeing different shades of truth. Which will speak to your truth?
So good! This book ought to be a bestseller. – Alberto Cairo, Knight Chair in Visual Journalism, University of Miami, author of How Charts Lie
An excellent book, and one that will be equally useful for journalists and political junkies alike. – Anthony C. Robinson, Penn State University
An excellent overview of thematic mapping. May it lead to a better understanding of the ways to visualise and interpret maps. – Lauren Tierney, Washington Post
Ken’s first book set the stage for better cartography. This book will undoubtedly take you to the next step to better mapmaking and truth telling. – Jon Schwabish, PolicyViz and Urban Institute
A really great and exhaustive (in a good way!) way to explore one dataset. – Rosemary Wardley, National Geographic
This book's focus on one consequential dataset can teach you to read and make maps more carefully. – Amy Griffin, RMIT University
This book is amazing! – RJ Andrews, Info We Trust
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