Dataviz book


My book Data Visualization: charts, maps and interactive graphics is coming out on 19 September 2018.

You can pre-order it with 30% discount here! Just use the discount code ASA18.

It is published by CRC Press and is part of the CRC-ASA series on Statistical Reasoning in Science and Society. There are several good books available on dataviz, so I wanted to make sure this offers readers something different. It is a broad overview, covering many statistical techniques in terms of how they can be visualized. Most contemporary dataviz books come from a design or journalism background.

It is short, affordable and accessible to all: no algebra. There is a series of short chapters, each focused on one specific task, such as time trends, maps or interactivity. You can read a chapter in a coffee break, so you can easily start to build your awareness of dataviz.

Click here to view the Table Of Contents.

I have three audiences in mind:

  • The data analyst who was never taught about good visualisation and wants to expand their skills
  • The budding dataviz designer, whether you are at high school and considering careers, or coming to the end of studies in statistics, design or web development.
  • The boss who has to hire, or commission, someone to make dataviz for his/her organisation, monitor their progress and be assured of good results

The making of...


Here's where you can find all the code I used to generate my own images in the book. Prior to publication, I'll load it up in conjunction with my blog posts expanding on various images from the book, and when the book comes out, it will all go up here. There is a corresponding GitHub repository for those of you who like that kind of thing.

Chapters:

Table of contents

Click here for a detailed table of contents in PDF

    Section I: The basics
    1. Why visualize?
    2. Translating numbers to images
    Section II: Statistical building blocks
    3. Continuous and discrete numbers
    4. Percentages and risks
    5. Showing data or statistics
    6. Differences, ratios, correlations
    Section III: Specific tasks
    7. Visual perception and the brain
    8. Showing uncertainty
    9. Time trends
    10. Statistical predictive models
    11. Machine learning techniques
    12. Many variables
    13. Maps and networks
    14. Interactivity
    15. Big data
    16. Wrapping up the package in a report, dashboard or presentation
    Section IV: Closing remarks
    17. Some overarching ideas

Chapter 1: Why visualize?

Check back after 19 September for The Making Of...

Chapter 2: Translating numbers to images

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Chapter 3: Continuous and discrete numbers

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Chapter 4: Percentages and risks

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Chapter 5: Showing data or statistics

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Chapter 6: Differences, ratios, correlations

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Chapter 7: Visual perception and the brain

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Chapter 8: Showing uncertainty

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Chapter 9: Time trends

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Chapter 10: Statistical predictive models

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Chapter 11: Machine learning techniques

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Chapter 12: Many variables

This R script file accompanies my blog post on the Saturn images. The rest of the chapter will appear here after publication on 19 September 2018.

Chapter 13: Maps and networks

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Chapter 14: Interactivity

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Chapter 15: Big data

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Chapter 16: Wrapping up the package in a report, dashboard or presentation

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