A review of How Charts Lie by Alberto Cairo

Stephen Redmond

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TLDR: This book is an excellent resource for beginners (and even many experienced practitioners) in the data visualisation field which gives a sound foundation on how charts work and then into the practices we need to avoid when creating charts to inform or persuade. Data visualisation is a powerful technology that can be used to either tell a truthful story or can be used to deliberately hide the facts. With great power does come great responsibility and Alberto concludes the book with a call for all of us to adopt good ethics and to become part of society’s immune system rather than part of the illness. I heartily recommend the book to all readers.
Declaration: I requested to receive a free copy of this book (valued at GBP£17.99) from the publishers for me to prepare this review. I have not received any other benefit or influence and my review is independently prepared.

Alberto Cairo has been a leading character in the data visualisation community for many years. He has educated many in the community via his both his work at the University of Miami and his MOOC delivered via the Knight Centre for Journalism at the University of Texas. He has written many articles and published two previous books on the topic that have been very well received. His book, The Truthful Art, is an excellent resource to teach the end-to-end process of data visualisation.
In this book, Alberto tackles the subject of poor-practice in chart creation. Much of this poor practice is not deliberate, often being due to the lack of knowledge from the practitioner, while some of it is very much deliberate and ethically questionable.
Right from the introduction Alberto dives into some of the greatest bug-bears of many visualisation professionals — including one of my least-favourite practices, the mis-use of choropleth maps. Even just having read the introduction you will have learned a lot.
The first chapter is an introduction into how charts work — the various encodings that are used to help us understand data. This is very important for us to know in order to realise how these encodings can be mis-used. This is a chapter that will be important to practitioners to understand, and I would also recommend it to students who are new to the topic as a base learning to aid in their future researches.
The subsequent chapters look at various ways in which charts can be misused and goes into detail explanations of each, with good warnings about which practices that one should avoid. Many good examples are provided and explained. Chapter 5 is especially good in this regard in that it explains how to understand charts that explain uncertainty — such as the, very topical, cone of uncertainty used to suggest the possible track of a hurricane.
The conclusion is well presented and extols us to the virtue of not misusing charts. Data visualisation is a technology that can be used for good or bad, and we should hold ourselves to always trying to use it for good. There is a journalistic ethical principal of verification (not always practiced by all journalists!) that should become a civic principal for us all to follow. Use the hammer to build, not destroy!
There were times where I felt that some pieces may have been over-explained, but that may not be a bad thing, but overall, I found the book to be a very good read and I feel it will be an excellent resource for practitioners into the future.

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Stephen Redmond

Stephen Redmond, Big Data, AI & Data Viz Professional. MSc in Data Analytics. Qlik Luminary. Author and blogger. All opinions my own.