Author: Claus O. Wilke
Publication date: 30 April 2019
Publisher: O’Reilly Media
Number of pages: 390 pages
Data visualization is part art and part science. The challenge is to get the art right without getting the science wrong, and vice versa.
Claus O. Wilke in Fundamentals of Data Visualization
Select data – click ‘Insert’ – click ‘Recommended Charts’ – pick the chart that you like – click OK. Then, play with colors and fix the labels.
We are familiar with create and modify our data presentation in that way, particularly in Excel. We think that establishing a chart is an easy peasy work because mostly we let the program work for us. The saddest part is, how many of us considering the bias that may lead from our visualization? Also, how many of us thinking about people with color-vision deficiency as our audience so we have to pick colors wisely and make it color blind-friendly visualizations?
Why I love this book?
This book is a fantastic resource to understand the key principles, methods, and concepts to present data in the most unambigous, unbiased, and inclusive way. It is majorly divided into three parts: from data to visualization, principle of figure design, and other aspects that did not fit to the first two sections. Readers could learn from abundant charts because Wilke is not only presents the correct data visualization, but also some troublesome figures that classified into wrong, ugly, or bad.
Wrong means the chart is mathematically problematic; ugly means the chart is aesthetically unpleasing; while bad means the figure is unclear, sophisticated, and lead the reader to have issues in understanding the data. Wilke explains his argument for creating such categories. It has been fun to learn from mistakes and make a guess for the reason to test our own understanding. In addition, it is not rare that I was surprised that some of them are familiar enough without acknowledging that they are principally wrong.
Wilke build this book not based on the chart type but rather by the type of the data, such as how to present amounts, distributions, relationships, geospatial, and uncertainty. In this way, he unfolds that presenting data in a chart is not a stiff task yet it is a dynamic work. What actually matters is how to create graph that is not bias and not overwhelming the reader without unnecessary cognitive load so we can tell what story we would like to bring under the light by helping the reader to perceive it.
We simply think that the aesthetics of a data presentation is not really crucial. This book might change the reader’s mind significantly. The concept of proportional ink (also explained in book Calling Bullshit: The Art of Skepticism in a Data-driven World), the do’s and don’ts of data information, and how to pick the best colors for color blind audience is well-explained and illustrated.
I am extremely recommend this book to anyone working with data; from the simplest data to the ones with big data.
Ps: you can read this book for free (and of course legal in this link)
