Tips for creating more compelling data visualizations

How to draw viewers to your points of interest

In this example from Nathan Yau's book Data Points: Visualization That Means Something, Yau shows how to ensure your viewers' eyes are drawn to points of interest. Excerpted with permission from publisher Wiley, copyright 2013 all rights reserved.

When you look at a visualization for the first time, your eyes dart around trying to find a point of interest. Actually, when you look at anything, you tend to spot things that stand out, such as bright colors, shapes that are bigger than the rest, or people who are on the long tail of the height curve. Orange cones and yellow signs are used to alert you on the highway of an accident or construction because they stand out from the monotony of the black pavement. In contrast, Waldo is hard to find right away because he doesnt stand out enough to stick out in a sea of people.

You can use this to your advantage as you visualize data. Highlight data with bolder colors than the other visual elements, and lighten or soften other elements so they sit in the background. Use arrows and lines to direct eyes to the point of interest. This creates a visual hierarchy that helps readers immediately focus on the vital parts of a data graphic and use the surroundings as context, as opposed to a flat graphic that a reader must visually rummage through.

For example, Figure 1 is a scatterplot that shows NBA players usage percentage, an estimated percentage of possessions that a player is involved in while on the court, versus points per game. The dots, fitted line, grid, border, and labels are of the same color and thickness, so there is no clear visual focus. Its a flat image, where all the elements are on the same level.

Figure 1: All visual elements on the same level

This is easily remedied with a few small changes. In Figure 2, the line width of the grid lines is reduced so that they are no longer as thick as the fitted line. In this example, you want the data to stand out. The grid lines also alternate in width so that it is easier to see where each data point lies in the coordinate system, and theres no imaginary blur that you get in the original chart.

Scatterplot, grid lines reduced
Figure 2: Width of grid lines reduced to fit in background
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