Avoiding Data Pitfalls

Chapter SevenPitfall 6: Graphical Gaffes

“Visualization gives you answers to questions you didn’t know you had.”

—Ben Schneiderman

How We Visualize Data

There are two reasons I wanted to write this book in the first place. The first reason is that I noticed students in the data classes I teach were making a lot of the same mistakes on their assignments that I had made when I started my own data journey many years ago. What if there were a book that pointed out a number of these common mistakes to them? Would my students make these errors less often? Would I have made the same mistakes less often if I had read such a book back when I first started?

I'm not just talking about creating bad charts, though. I'm talking about the types of mistakes we've covered thus far – thinking about data and using it inappropriately, getting the stats and calculations wrong, using dirty data without knowing it – you name it.

That leads me to the second reason I wanted to write this book. It seemed to me that a large portion of the conversation about data visualization on social media was centering on which chart type to use and not use, and how to get the visual encodings and channels right.

Poor maligned chart types like the pie chart and the word cloud were getting bullied at every corner of the “dataviz” online playground. Everyone who was “in the know” seemed to hate these chart types as well as a few others, like packed bubble charts. Some even declared them to be “evil,” and others signaled ...