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Use of Color in Data Visualization
Use of Color in Data Visualization

Color should bring meaning to your data. Restrained and consistent use of color will make it easier for your audience to understand.

Zach Gemignani avatar
Written by Zach Gemignani
Updated over 3 years ago

More often than not, dashboards and reports get lit up with color like an over-dressed Christmas tree. The color is applied indiscriminately and adds little to the meaning of the dashboard. Appropriate use of color requires restraint.

Color can draw your eye to what is important and tie together similar things. For example, if we increase color brightness, it will attract attention and make a point seem more important. Similarly, use of the same color hue can be used to connect things that are related.

Color can communicate emotion and feeling. For example, red can be associated with positive feelings like excitement and desire, but also with negative feelings of danger and alarm. One common use for color in data visualization is using red for negative/loss (like a loss of money) and green for positive/gains. If you were to have a green arrow pointing down to show loss and a red arrow pointing up to show gains, that would be confusing.

The meaning of color differs by culture. For example, in the U.S., white is the color worn by brides to symbolize purity. In China, white symbolizes mourning and death, and red is the color for brides and celebration.

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Colors can be broken into high-level dichotomies such as “earth-tones” versus “unnatural” colors. We perceive earth-tones as calming (Edward Tufte has said that these are the kinds of colors you want to use if you just want to use color very gently on your page). In contrast, unnatural colors jump out at your audience, making them ideal for showing an alert.

Color to display data
When you are using color in your graphs to represent data, there are three types of color schemes to consider:

  • Sequential when you are ordering values from low to high.

  • Divergent when the values are ordered and there is a critical mid-point (e.g. an average or zero).

  • Categorical when data falls into distinct groups (e.g. countries) and therefore requires contrast between adjacent colors.

gradient-values-e1328906861195.png

This presentation about Color and Contrast in Data Visualization provides an overview of good principles.

Color and Contrast

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