Data Centric Book Review: Effective Data Visualization

Several years ago, I stumbled across two data visualization blogs that changed the way I think about data presentation. One was by Ann Emery and one was by Stephanie Evergreen. They both have a ton of excellent blog posts walking you through how to improve basic Excel charts in a totally approachable way.

The big picture is that Excel’s default charts are not great, but with some effort you can customize those defaults, or even create new kinds of charts, to be powerful storytelling visuals.

After a year of learning from those blogs, I found myself having to google or search through the archives for a post I vaguely remembered when I needed to create a certain visualization type. So, I was really excited to see that Stephanie Evergreen’s book, “Effective Data Visualization,” pulls together many of those tutorials and more.

I have everything I need at my fingertips and with a few strategically placed post-it notes for some of the more complicated strategies, it has been hugely useful in my current work. I purchased the 1st edition of the book several years ago, but Evergreen has since released a 2nd edition with additional tips and chart types.

Overview

Stephanie Evergreen’s book is divided into sections based on the type of data you are visualizing (i.e., a single number, trends over time, benchmarking against a goal, survey data). This format makes it easy to explore appropriate chart types for your data. I read the book straight through as though it were a novel, but you certainly don’t have to. You can just find the chapter that is relevant for your data and skim until you find a chart to try.

More importantly, the language in the book is lighthearted and relatable. The book isn’t a dense, dry read. There are enough pictures and screenshots to make sure the steps of the process are clear and Excel Ninja Level ratings to let you know how complicated any particular visualization is.

Here are the five most interesting things I learned from the book:

1. My first post-it note in the book is on the slopegraph section. You may have seen this before but not known its name, or maybe you’ve never seen it at all. It looks like a line chart with only two time points or categories. Combined with strategic color use, it can make a complicated data set easy to understand.

2. My second post-it note in the book is on the section for dot plots. These are not a very commonly used chart type, but they don’t take a lot of effort to understand. They can convey the same information as a clustered bar chart, but are less visually overwhelming because they contain color in just a small circle rather than a long bar or column. I’ve used these to display voter turnout and achievement gap data.

3. There is a section on icons and icon arrays that I liked because I hadn’t thought of them as data visualizations before. Icons can be really powerful and research shows that images related to your data help people remember the data. I recently added icons to the contact section of my resume to break up the text, and I think it catches the eye better than an email address alone.

4. Benchmarking graphs are bar or column charts that have an additional marker or line for a target. When combined with performance data in bars or columns, the line provides additional context to really guide action steps based on the data. It’s good to know that 82% of your students are proficient in reading, but how does that compare to the state average or benchmarking target? By adding in those additional data points, you paint a whole picture of reading proficiency in your school.

5. Lastly, there are small tips throughout that can be applied to many chart types, but one I hadn’t seen before was using a customized label for data by linking the data label cell to a text box containing your custom data label text.

For example, in the image below, I selected just the first data label box, which originally said 82%. Once that was selected, I clicked into the formula box. Then I typed = and clicked into cell B8, which contains the custom label I wanted for that bar.

If you are committed to advancing your data visualization game and want to be walked through the process, I recommend this book. Although some of the techniques I’ve used enough to remember on my own, I do refer to the book for many of the charts that I like to use now. Although the charts aren’t hard to make, having the steps laid out of how to structure the data table and format it makes the process easy.

What is your favorite place to learn new data visualization strategies?