This book takes the reader through the process of learning and creating data visualisation, starting with a selection of basic principles. Each easy-to-follow chapter poses one key question and provides an array of valuable answers, including data visualisation examples throughout.
This book takes the reader through the process of learning and creating data visualisation, starting with a selection of basic principles. Each easy-to-follow chapter poses one key question and provides an array of valuable answers, including data visualisation examples throughout.
Neil Richards is a data visualisation specialist and enthusiast with over twenty-five years' experience in the data industry. Through his regular personal creative data visualisation projects, he has been awarded the title of Tableau Visionary (formerly Tableau Zen Master) a total of four times, and is a regular speaker at data visualisation conferences and user groups. Formerly Knowledge Director for the Data Visualization Society, he also sits on the Board of data visualisation non-profit Viz For Social Good. Neil works as a Lead Business Intelligence Analyst at JLL and has a BSc. in Mathematics and a BA in Environmental Studies. He lives in Derbyshire in the United Kingdom.
Inhaltsangabe
Preface. Author. Introduction. SECTION I First Questions. Chapter 1.1 Should the data drive the visualisation? Chapter 1.2 What's in a colour? Chapter 1.3 What does data visualisation have in common with psychology? Chapter 1.4 Do data visualisations have to tell a story? Chapter 1.5 Is it OK to steal? Chapter 1.6 Is white space always your friend? Section II Challenging. Questions Chapter 2.1 Why do we visualise data? Chapter 2.2 Why do we visualise using triangles? Chapter 2.3 Does it matter if shapes overlap? Chapter 2.4 What is data humanism? Chapter 2.5 What is design-driven data? Chapter 2.6 Do we take data visualisation too seriously? Chapter 2.7 Why create unnecessary data visualisations? Chapter 2.8 When are several visualisations better than one? Chapter 2.9 What can I do when data is impossible to find? Section III Idea Questions. Chapter 3.1 What is the third wave of data visualisation? Chapter 3.2 What alternative ways are there for visualizing timelines? Chapter 3.3 Why do I use flowers to visualise data? Chapter 3.4 What are Data Portraits? Chapter 3.5 How can I take inspiration from album covers? Chapter 3.6 How many ways can you tile the United States? Chapter 3.7 Is it possible to tile the world? Chapter 3.8 Can you create visualisations using only numbers? Chapter 3.9 How do you visualise music? Chapter 3.10 What are Truchet tiles? Chapter 3.11 How do you create 31 visualisations in a month? Index.
Preface. Author. Introduction. SECTION I First Questions. Chapter 1.1 Should the data drive the visualisation? Chapter 1.2 What's in a colour? Chapter 1.3 What does data visualisation have in common with psychology? Chapter 1.4 Do data visualisations have to tell a story? Chapter 1.5 Is it OK to steal? Chapter 1.6 Is white space always your friend? Section II Challenging. Questions Chapter 2.1 Why do we visualise data? Chapter 2.2 Why do we visualise using triangles? Chapter 2.3 Does it matter if shapes overlap? Chapter 2.4 What is data humanism? Chapter 2.5 What is design-driven data? Chapter 2.6 Do we take data visualisation too seriously? Chapter 2.7 Why create unnecessary data visualisations? Chapter 2.8 When are several visualisations better than one? Chapter 2.9 What can I do when data is impossible to find? Section III Idea Questions. Chapter 3.1 What is the third wave of data visualisation? Chapter 3.2 What alternative ways are there for visualizing timelines? Chapter 3.3 Why do I use flowers to visualise data? Chapter 3.4 What are Data Portraits? Chapter 3.5 How can I take inspiration from album covers? Chapter 3.6 How many ways can you tile the United States? Chapter 3.7 Is it possible to tile the world? Chapter 3.8 Can you create visualisations using only numbers? Chapter 3.9 How do you visualise music? Chapter 3.10 What are Truchet tiles? Chapter 3.11 How do you create 31 visualisations in a month? Index.
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