Have you noticed it as well? The tide is turning against dogmatism in data visualization, as witnessed by the increasing number of voices speaking out against a rigid approach and closed-mindedness regarding practices that are often ridiculed in knee-jerk fashion. It’s about time.

To which voices am I referring, and which data visualization practices are they defending?

1. Charts with non-zero y-axes

Can you tell Vox’s Johnny Harris and Matthew Yglesias have had it with readers taking pot shots about their choice of y-axis starting points? Their well-reasoned video entitled “Shut up about the y-axis. It shouldn’t always start at zero” says it all:

Harris and Yglesias show that the choice of axis starting point depends on the context, the unit of measure, and on the comparison being made.

2. Artistic approaches to data visualization

In Andy Cotgreave’s recent ComputerWorld article “Why Do We Visualise Data?“, Andy argues that not all data visualizations need to be burdened with the requirement of imparting ultimate precision of comparison. It depends on the purpose.

“The purpose of a visualization will also determine the extent to which you should inform effectively…Sometimes it’s more important to make someone engage with the overall message rather than the minutiae.”

Andy uses the example of Stephanie Prosavec’s “Air Transformed“: a wearable data visualization necklace showing air quality in Sheffield, UK:


Should this project really be ridiculed as “ineffective” and horribly contrary to “best practices”, with no place for it at all in the field of data visualization? Or could it be that this form of expression engages human beings in a way that a rigorous report complete with bar charts and compliant zero y-axis timelines of air quality in Sheffield could hardly do? Maybe both the report and the necklace are valid, each in their own way.

Which should you create? It depends on your purpose and your audience.

3. Pie charts

Oh, the poor, maligned pie chart. The chart type that gets pushed around and bullied on the data viz playground more than any other. Randal Olsen of /r/dataisbeautiful ran a twitter poll asking “Do you think pie charts should be banned from #dataviz?”. Scientific or not, nearly 2 in 5 responded affirmatively:

That’s amazing if you stop and think about it. Almost 40% of respondents, likely mostly data viz enthusiasts who follow Olsen, think that pie charts should never, ever, ever be used. Hilariously, Andy Kirk of Visualising Data asked whether we should also run a poll about whether those people should be banned, and Irvin Almonte’s response was sheer genius:

Again: It depends. Say it with me: IT DEPENDS.

Pie charts, in certain instances, can actually be more effective than bar charts at showing specific part-to-whole comparisons. And if the part-to-whole relationship is far more important to your message than comparing uber-accurately between categories, and if there are a very small number of slices, go ahead, give thought to using a pie chart. Don’t be intimidated by pie chart haters. There, I said it.

4. Word Clouds

I entered the fray last week with my blog post “My 3 Basic Tenets of Data Visualization” in which I argued that rules of thumb, not black-and-white rules, should prevail, along with a spirit of humility and openness to exploration and innovation in data viz.

I also did the unthinkable: I defended the Word Cloud. The poor, lowly pal of the pie chart, united on the playground in mutual fear of the roving data-dogma bully. My point is that if you only had a very short amount of time to impress upon a large room of people the most commonly used passwords, which of these four visualization types would you choose?

The word cloud sacrifices precision for completeness (all of the passwords actually appear on the screen in only the word cloud) and readability (the most commonly used passwords almost shout out at the reader). Is that a reasonable trade-off to make? Maybe. It depends.

Since that blog post, “What are your most used words on Facebook” has gone viral, and we’ve been inundated with over 16 million word clouds as of the writing of this blog post. Of course one can only hope this app is not a gigantic phishing scam, but do you think a bar chart version of your most commonly used words, or a concise and thorough text analytics report would have also gone viral? Maybe, but probably not. And I’m not saying “going viral” is a end that justifies all means, but in this case, ultimate precision of comparison is probably not needed anyway. It actually worked a little too well.

Let’s not let the pendulum swing too far, though.

This casting-off of suffocating restraint and a fearful spirit of ridicule is a REALLY GOOD THING in data visualization, but let’s not let the pendulum swing too far the other way. It’s true that pie charts are very often the wrong choice, and the majority of the time a y-axis that starts at zero is a really good choice.

I’m not a big fan of the word “best” in “best practices”, which seems to promise some optimal solution, but I do like the sentiment in this response by Vance Fitzgerald to my question on twitter about rules of thumb in data visualization:

I’m hopeful that the next phase of data visualization is one that embraces the gray of “it depends” and encourages open dialogue and constructive criticism. In order to get there, we’ll definitely have to shed dogma. Let’s absolutely do so, but let’s also carry forward the principles and rules of thumb that just make good sense, while being open to the possibility that breaking those rules might be a great idea in specific situations.

Wouldn’t this be a more mature approach? Wouldn’t it also be more welcoming, and more enjoyable?

Thanks for reading,