Copyright

Make It Visible: Visual Analytics and Data Storytelling

Published by Margin of Error Media LLC, Spokane, Washington.
marginoferrormedia.com

No part of this book may be reproduced, distributed, or transmitted in any form or by any means without the prior written permission of the publisher, except for brief quotations in reviews or scholarly work with full attribution.

For permissions, classroom adoption, or bulk purchase, write to patilv@gmail.com.

First edition, 2027.
ISBN, hardcover: [ISBN-PENDING]
ISBN, paperback: [ISBN-PENDING]
ISBN, Kindle: [ISBN-PENDING]

The online edition is at viz.marginoferrormedia.com. Corrections are collected at github.com/patilv/make-it-visible-feedback.

Data and Figures

Every figure in this book was drawn by the author in R with ggplot2, from public data. Each caption names the source. The datasets, the scripts that prepared them, and the code behind every figure are published with the online edition so that any figure can be reproduced and any claim checked. Data providers named in the captions include the United Nations Inter-agency Group for Child Mortality Estimation, the Institute for Health Metrics and Evaluation, the UN Refugee Agency, the US Census Bureau and the American Community Survey, the Vera Institute of Justice, the World Values Survey, FiveThirtyEight, the National Center for Charitable Statistics, the UN World Population Prospects, and the Human Mortality Database, in several cases through the archives of Our World in Data and TidyTuesday. None of them has endorsed this book.

Text is set in EB Garamond. Headings, figure text, and code are set in IBM Plex Sans and IBM Plex Mono.

A Note on AI

This book was written with a language model as a working partner. I used Claude, made by Anthropic, to draft and revise passages, to check reasoning, to write and debug the R code behind the figures, and to build the publishing pipeline that turns one set of source files into this print edition, the online edition, and the Kindle edition. A project of this size would not have been feasible for one author without it.

The judgment in the book is mine. I checked every figure against its data and read every claim about a number against the chart that shows it. My views on what a chart should do for its reader come from years of teaching the topic and from building charts for people who had to use them. Where the book is wrong, the fault is mine, and I would like to hear about it at the address above.

Chapter 12 describes the method, and I applied it to this book. The model drew first drafts, and I marked every claim the data did not support. Each marked claim was removed or rewritten.