Colors can make or break a chart. Colors direct our eye movements, and therefore our brains and attention. It’s up to you: will you help or hinder your reader’s understanding?

Here are some simple strategies for communicating clearly with chart color.

Strategy 1: Select a custom color palette.

Rather than using Excel’s default colors, match your chart to the organization’s logo. (Consultants: Match your client’s logo, not your own.) For my grad school projects, I align everything with my university’s logo.

Does the organization have a super basic color scheme? My grad school’s logo is green and yellow, which doesn’t give me many options to work with. So, I found a similar color palette on design-seeds.com. I used the instant eyedropper to find each color’s RGB code. Now I’ve got six colors to play with instead of just two.

chart_colors

Strategy 2: Figure out if your categories are nominal, sequential, or diverging.

Nominal or categorical variables are things like race/ethnicity (African American, Asian, Latino, White, etc.) or gender (male or female). Think about which pattern you want to emphasize, and use darker action colors to draw attention to that finding.

nominal_before-after

Sequential or ordinal categories have a natural order, like age ranges (5-9 year olds, 10-14 year olds, and 15-19 year olds) or years (Year 1, Year 2, and Year 3 of an evaluation). Sometimes categories go from less to more or from nothing to something. An example of a nothing to something progression is a satisfaction survey question that asks program participants to assess how likely they are to recommend the program to a friend (not at all likely, somewhat likely, very likely). For these charts, the action color can represent the something and white can represent the nothing:

sequential_before-after

Divergent categories are opposites, like agree/disagree scales on surveys. An example is a similar satisfaction survey question that asks participants to indicate whether they agree or disagree with the statement “I’d recommend this program to a friend.” When charting divergent variables, you might design a diverging stacked bar chart, as shown below. Select two different colors from your palette, like greens for agreement and yellows for disagreement. The extreme values (strongly agree and strongly disagree) get the darker colors.

diverging_before-after

(For a deeper discussion of these principles, check out colorbrewer2.org.)

Strategy 3: De-clutter by increasing white space and switching some black text to gray.

Which information is most and least important? Let’s de-clutter by removing or reducing anything without a crucial purpose. We want the reader’s attention focused on our most important patterns.

For example, if you’re using Excel, you might improve upon the default settings by deleting the border, the grid lines, or the tick marks. If you decide to keep the grid lines or tick marks, try adjusting them from black to gray so they fade into the background. You can also remove the legend and put labels within the chart itself (like that first bar chart with race/ethnicity information). Finally, you can outline shapes in white to give the chart a crisper look and feel (like the diverging stacked bar chart shown above).

Do you have additional color tricks to share? Please share your comments below.

Want to create one of these charts? Download my Excel file. Or, want a step-by-step tutorial? Stay tuned: Next week’s dataviz challenge is a diverging stacked bar chart!