The Practical Charts BOOK will be available on Nov. 15!

September 13, 2023 Nick Desbarats

At embarrassingly long last, I’m relieved to announce that the Practical Charts book is finished! The book will be released on November 15th, with pre-orders beginning in a week or two.

The goal of the book is as ambitious as the course on which it’s based: to teach chart creators of any experience level to create expert-level charts in just a few days. Given how many common data visualization challenges and mistakes need to be tackled to accomplish that, it was a tall order to keep the book down to 300 pages, but, flipping through the advance copies that I just giddily unwrapped, I think it might actually deliver. You tell me, though, when you read the book (you’re gonna read it, right?). More details about the book can be found on the official Practical Charts book page.

There will be more book-related announcements in the coming weeks, so make sure you’re subscribed to my email list to be notified when…

Pre-orders can be placed so you get the book shipped to you automatically on the release date (you might even get an extra goodie or two from me if you let me know that you pre-ordered it).
Bulk orders for team leaders and educators are available (which will be before November 15th).
Free advance reviewer copies can be requested (we’ll be sending out a limited number of free advance reviewer copies so that there are reviews on Amazon when the book is released).
Sneak peeks of content from the book are released.

Also, make sure you're subscribed to my email list if you’re interested in becoming a “VIP Reader” of the book. WTH is a “VIP Reader”? Well, VIP Readers will receive perks such as preferential consideration when requests for free advance reviewer copies of the book are being considered, and access to private “ask me anything” Zoom group calls just for VIP Readers. In exchange, I’ll be asking VIP Readers to pre-order the book (so that Amazon’s algorithms quickly learn who to show the book to), then post a review on Amazon and chat up the book on their social media channels when the book is released in November. Interested? Awesome! I expect to put out the call for VIP Readers in one to two weeks via my email list.

Connected scatterplots make me feel dumb. (article in Nightingale)

September 5, 2023 Nick Desbarats

Connected scatterplots are sometimes used to show how two variables are related over time. In my latest article for Nightingale (the journal of the Data Visualization Society), I argue that connected scatterplot are virtually never the best choice, and alternatives like stacked line charts and indexed line charts can communicate the same insights as connected scatterplots, but are much easier to read and less prone to misinterpretation.

There are no bad chart types... Right?

July 19, 2023 Nick Desbarats

There are about a dozen chart types that I don’t recommend using for “everyday” charts in reports and presentations, such as bullet graphs and box plots. Some people are uncomfortable with the idea of saying that a given chart type is never the most effective choice, however. In this blog post, I argue that there’s no reason to think that, for every chart type, there must be situations in which it’s the most effective choice, and that it’s entirely possible that some chart types are never the most effective choice.

Should you learn dataviz theory?

June 20, 2023 Nick Desbarats

Occasionally, I come across a claim on social media that, in order to become truly competent at dataviz, you need to know about theoretical concepts such as graphical objects, encoding channels, and preattentive attributes of visual perception.

Is that true, though? Or can you still create effective charts without knowing about those theoretical concepts?

Choosing a chart type is harder than you think

May 23, 2023 Nick Desbarats

Many chart creators assume that choosing a chart type is an easy decision that can be made using simple rules of thumb like, "Use line charts to show data over time." Unfortunately, these rules of thumb are too simplistic and often lead to poor chart type choices, and making a good chart type choice usually requires taking at least six or eight factors into consideration.

Will AI automate data visualization?

March 28, 2023 Nick Desbarats

As pretty much everyone and their robot dog is now aware, there are jaw-dropping breakthroughs happening in artificial intelligence (AI) on an almost daily basis. To those of us in the data visualization field, this begs the obvious question: Will AIs be able to create expert-level charts without any human intervention, and, if so, when might that happen?

"I'm using data storytelling, but my charts are still poorly received. Why?"

March 8, 2023 Nick Desbarats

Unfortunately, there seems to be a widespread belief that a lack of data storytelling is always the main—or possibly only—reason why charts and data presentations don’t go over well with audiences, and that turning charts and data presentations into “data stories” virtually guarantees that they’ll be effective and well received. Even though that view isn’t promoted by most data storytelling thought leaders, it seems to have taken hold among many data professionals anyway.

Thoughts on Alberto Cairo's "The Art of Insight"

March 2, 2023 Nick Desbarats

Thoughts on a draft manuscript of Alberto Cairo’s upcoming book, The Art of Insight.

Labelling all the values in a chart doesn’t make a bad chart better

January 11, 2023 Nick Desbarats

Chart creators often try to make unclear charts clearer by labelling all the values in the chart. This sounds like a good solution in theory, but, in practice, charts that rely mostly or entirely on reading textual value labels are far slower and more effortful to read than charts that communicate key insights primarily through graphics (bars, lines, color shades, etc.)

Why I Stopped Using Bullet Graphs (and What I Now Use Instead)

November 3, 2022 Nick Desbarats

After teaching many data professionals about bullet graphs and using them in many dashboards, I started to notice that they had a fair number of downsides. A few years ago, I started using an alternative called “action dots” that, I believe, are more informative, easier to understand, faster to visually scan, more compact, easier to implement, and don’t have any of the downsides of bullet graphs.

Are vertical line charts ever a good idea?

June 29, 2022 Nick Desbarats

I recently asked dataviz Twitter if there were situations in which a vertical line chart was the truly best choice. I was skeptical at first, but they changed my mind, so I wrote up the thought process as a Nightingale article for those who may be considering using vertical line charts in their own work.

Are line charts liars?

June 7, 2022 Nick Desbarats

When I show line charts in my Practical Charts workshops, participants sometimes express concern that line charts “hide values that occur in between the points on the line”. In this article, I argue that this is a misconception and that line charts of summary values (e.g., monthly totals) don’t hide meaningful information.

How many bins should my histogram have?

April 5, 2022 Nick Desbarats

Choosing how many bins to include in a histogram can be a tricky design decision. There are many articles out there that recommend algorithms or rules of thumb for calculating the “optimal” number of bins, however, I don’t think that any calculation can do this reliably. In this post, I argue that the “optimal” number of bins depends mostly on the specific insight that needs to be communicated about the data, and not on the nature of the data (number of values, standard deviation of the values, etc.)

Let's Make a Map of the Data Visualization Field!

February 4, 2022 Nick Desbarats

I love data visualization but, TBH, the field is a bit of a mess and can be overwhelming and unapproachable, especially for beginners. In an effort to bring a bit of order to the chaos, I've been working on a "map" that brings many dataviz-related terms, types of visuals, skills, software products and books together into a single graphic that attempts to show how they all relate to one another, and to make the field more approachable.

Why the NYT Spiral Graph Is a Failure. And a Success.

January 11, 2022 Nick Desbarats

A recent The New York Times graph showed COVID case counts in the U.S. since the beginning of the pandemic in a spiral chart. This chart basically burned data viz Twitter to the ground, with everyone and their dog either praising or trashing it. I think that a crucial element was missing from most of the debates, though, which I discuss in this article.

Does Data Visualization Have Rules? Or Is It All Just “It Depends”?

December 17, 2021 Nick Desbarats

In the data visualization community, there are those who believe that there are universal rules such as “Never use pie charts”, or, “Always include zero in a chart’s scale”, and then there are those who believe that there are no universal rules that apply in all situations, only general principles that must be adapted to the specific situation at hand based on judgment and experience. I propose a third possibility, which is that many common dataviz design decisions can be codified as formal rules that apply in all situations, it’s just that those rules tend to be too complex to be expressed as single sentences. They can, however, be expressed as relatively simple decision trees that can reliably guide practitioners of any experience level to the best design choice.

Do I need to include zero in my chart’s scale? (It’s surprisingly complicated…)

December 7, 2021 Nick Desbarats

Chart creators often extend the quantitative scale in their charts to include zero when it’s not necessary, or don’t extend it to zero when it is necessary. Making the wrong design choice can make charts hard to read, distort readers’ perception of the data, or hide key insights. Expert opinions differ on when it is and isn’t necessary to extend a chart’s scale to zero, but most of the opinions that I’ve seen are, I think, too simplistic. Determining when zero is or isn’t necessary is surprisingly complex and multi-factorial (hence this 4,600-word article), but it can be captured as a decision tree of rules that chart designers of any experience level can follow to guide them to the right choice in any situation. Feel like coming down the rabbit hole with me to find out what are all of the factors that affect this decision?

The biggest misconception in data visualization

November 16, 2021 Nick Desbarats

When designing a chart, most people try to come up with the ‘best way to visualize the data’. This often results in charts that are unobvious or useless to readers, though. Instead, we should try to design charts that best answer a specific question or that best communicate a specific insight about the data, even though such charts don’t answer all questions that readers might have about the data.

I’ve Stopped Using Box Plots. Should You?

November 4, 2021 Nick Desbarats

I've recently published an article in the Data Visualization Society's excellent Nightingale publication, entitled "I've Stopped Using Box Plots. Should You?" A brief summary:

After having explained how to read box plots to thousands of workshop participants, I now believe that they’re poorly conceived (box plots, not workshop participants ;-) ), which makes this classic chart type unnecessarily unintuitive, hard to grasp, and prone to misinterpretation. This has caused innumerable distribution-based insights to fail to land with audiences who weren’t willing or able to grasp them. Alternative chart types are virtually always easier to learn how to read, more informative, or both.

Want to read the full, heretical article? It's now available on the Nightingale site.

The two completely different chart types that are called "scatterplots"

September 21, 2021 Nick Desbarats

Should you label the individual dots in a scatterplot? Should you add a trendline? Should you divide the chart area into quadrants? The answers to these—and most other scatterplot design best practice questions—depend on which type of scatterplot you’re designing; a “correlation scatterplot”, or an “item-comparison scatterplot”.