5 Essential Principles for Clear Data Visualizations

Whenever I create a data visualization—whether a static chart, an interactive graphic, a report illustration, or a Twitter image—I follow five core principles.

Principle 1: Show the Data

Readers must see the data that supports the story. You don’t need to display every point, but you should highlight the data that backs your argument. For example, a US point‑density map based on the 2010 census shows each person as a dot, revealing population clusters without any borders, roads, or labels.

When a chart contains many series, use color strategically to highlight the series of interest or split a dense chart into several smaller ones.

Principle 2: Reduce Clutter

Unnecessary visual elements distract the audience and make the page look chaotic. Remove thick gridlines, overlapping markers, textures, gradients, and 3‑D effects that distort data. Simplify labels and avoid overloading the chart with text.

3‑D charts often introduce visual noise and data distortion; a plain 2‑D bar chart conveys the same information more clearly.

Principle 3: Combine Text and Graphics

Annotations are as important as the graphic itself. As New York Times data editor Amanda Cox says, “The annotation is the most important part…otherwise you’re just saying ‘look, it’s all there, figure it out yourself.’” Use three tactics: remove the legend and label data directly, write newspaper‑style titles that state the key takeaway, and add concise explanatory notes.

Principle 4: Avoid “Spaghetti” Charts

When a chart contains too many series, it looks like a tangled bowl of spaghetti. Break the data into small multiples (grid or panel charts) that share the same axes but display subsets of the data.

Small multiples have three advantages: once a reader learns to read one panel, the others become easy; they allow large amounts of information without confusion; and they enable cross‑variable comparisons.

Principle 5: Start from Gray

Begin every chart with all elements in gray. This forces you to add color, labels, and other highlights deliberately. In an example showing average years of education for ten countries, the gray baseline makes it clear which lines need emphasis.

By starting from gray, you decide purposefully which foreground elements to highlight, resulting in clearer, more persuasive visual stories.

Excerpt from the book Better Data Visualization Guide .