Good Charts Book in Three Sentences:

Scott Berinato in his Good Charts book provides an essential guide to how visualization works and how understanding context makes a chart a good chart. Scott emphasizes the process of understanding your context, finding your main idea, and visualizing it persuasively. He lays out a system for thinking visually and building better charts through a process of preparing, talking, sketching, and prototyping.

Good Charts summary:

“. . . for there is nothing either good or bad, but thinking makes it so.” —Shakespeare

Is a chart good? We don’t know. Without context, no one can say whether that chart is good or bad. It’s only well-built or poorly built.

To judge a chart’s value, you need to know more—much more—than whether you used the right chart type, picked good colors, or labeled axes correctly. Those things can help make charts good, but in the absence of context, they’re academic considerations.

Instead of worrying about whether a chart is “right” or “wrong,” focus on whether it’s good. It’s far more important to know:

  • Who will see this?
  • What do they want?
  • What do they need?
  • What idea do I want to convey?
  • What could I show?
  • What should I show?
  • Then, after all that, how will I show it?

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A Brief History of Data Visualization

Jacques Bertin, a cartographer, established two ideas that remain deeply influential to this day.

Expressiveness: Say everything you want to say—no more, no less—and don’t mislead.

Effectiveness: Use the best method available for showing your data. That is, choose the visual form that will most efficiently and most accurately convey the data’s meaning. If the position is the best way to show your data, use that. If color is more effective, use that.

We must learn to think visually, to understand the context, and to design charts that communicate ideas, not data sets.

And the best way to start learning how to produce good charts is to understand how people consume them. That starts by understanding some of the basics of visual perception.


When a Chart Hits Our Eyes

Everyone sees charts and decides whether they’re good or bad without a degree in visual perception theory.

Five broadly applicable ideas to understand what we see when we see a chart.

  • We don’t go in order: Visuals aren’t read in a predictable, linear way, as text is. Instead, we look first at the visual and then scan the chart for contextual clues about what is important.
  • We see first what stands out: Our eyes go directly to change and difference, such as unique colors, steep curves, clusters, or outliers.
  • We see only a few things at once: The more data that’s plotted in a chart, the more singular the idea it conveys. A visual that contains tens, hundreds, or thousands of plotted data points shows us a forest instead of individual trees.
  • We seek meaning and make connections: Our minds incessantly try to assign meaning to a visual and make causal connections between the elements presented, regardless of whether any real connections exist.
  • We rely on conventions and metaphors: We use learned shortcuts to assign meaning to visual cues on the basis of common expectations. For example, green is good and red is bad; north is up and south is down; time moves left to right.


A Simple Typology for Good Chart Making

When it comes to information visualization, the impulse is to immediately choose a chart type and click a button to create it. You should resist this impulse and instead start by thinking about the two questions that will make packing easier later on.

1. Is my information conceptual or data-driven?

  • Conceptual information is qualitative. Think of processes, hierarchies, cycles, and organization.
  • Data-driven information is quantitative. Think of revenues, ratings, and percentages.

2. Are my visuals meant to be declarative or exploratory?

  • A declarative purpose is to make a statement to an audience—to inform and affirm.
  • An exploratory purpose is to look for new ideas—to seek and discover.


Persuasion or Manipulation?

Used too aggressively or recklessly, persuasion techniques—emphasis, isolation, adding or removing reference points—can become deceptive techniques: exaggeration, omission, equivocation.

Judging whether your visualization crosses that indefinite line between persuasion and manipulation will, like all other ethical considerations, come down to a difficult, honest conversation with yourself.


  • Does my chart make it easier to see the idea, or is it actively changing the idea?
  • If it’s changing the idea, does the new idea contradict or fight with the one in the less persuasive chart?
  • Does eliminating information hide something that would rightfully challenge the idea I’m showing?


Present to Persuade

How you get a good chart to people’s eyes and into their minds is what matters most. An Effective presentation marks the difference between information visualizations that are merely adequate exposition and ones that move people.

Storytelling is the best, most powerful tool for making the kind of lasting impression that can create new understanding, change minds, or even affect policy change.

Powerful presentations that grab an audience don’t have to rely on clever chart types. They can rely on your ability to craft your idea as a little drama. Any story can be told in multiple ways, but a good way to start is to break the idea into three basic dramatic parts: setup, conflict, and resolution:


How to Practice Looking at (and Making) Good Charts

First pick out some charts to evaluate. Don’t pick only ones that you like or you think look cool. Pick all different kinds. Simple ones. Boring ones. Complex, artful ones. Ones on topics you know nothing about. Then follow this simple process for critiquing and workshopping them:

  • Make a note of the first few things you see: Don’t think—react. What stands out? Is it a peak? A color? Lots of words?
  • Make a note of the first idea that forms in your mind and then search for more: Decide what idea you think is being conveyed. Does it match the chart’s seeming intent?
  • Make notes on likes, dislikes, and wish-I-saws: Don’t focus on what you think is right or wrong. Instead, think about your gut reaction to the visual.
  • Find three things you’d change and briefly say why: Limit them to three so that you’re forced to prioritize only the most important changes. Saying “why” is key to making sure you focus on effectiveness rather than taste.
  • Sketch and/or prototype your own version, and critique yourself: Just as when you sketch and prototype your own data visualization, value speed over precision here. Include both positives and negatives in your self-critique.



Software will continue to get better, in the ways we can already see and in ways we can’t yet imagine. But what it won’t do—what it can’t do—is intuit your context. And context, still, is everything. Visual thinking and visual communication will become no less relevant no matter what features are added to software programs.

The process of understanding your context, finding your main idea, and visualizing it persuasively—that is, the guts of this book—will be the most critical skills you can develop to make Good Charts.

Grab a copy of Good Charts book.

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