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Why Color is Key in Data Visualization and How to Use It

When it comes to making charts, scales, and explaining data visually, using color is a very effective tool. Use it right, and you can not only draw your readers in, but you can help them better understand the underlying data.

So how can you use color in your data visualization and win? Here’s what to do, and what to avoid.

Sequential Color Scales

When you use color to represent a number, you need to create a scale. This is important—don’t use a scale for mapping categorical data (more on why later). Think of your scale as a gradient with a larger number on one end and a small number at the other. We can take advantage of some visual psychological here: We associate darker colors with density and density with greater numbers. Because of this, dark colors are perceived as being higher in value than lighter ones. So make sure you map the large end of you scale to a dark color and the smaller end to a light color. The bigger the difference between these two extremes, the more effective your use of color.

We can start with a simple black to white scale. By swapping black for another dark color we make things a bit easier to look at. Now instead of white, make the other end of the scale yellow. As you shift towards dark blue, your scale slowly changes and becomes a sea green in the middle. This is an example of a multi-hue scale, and is actually easier to read, understand because you’ve encoded you colors with changes in both hue and lightness.

If your chart is on a light background, it’s best to start with a cool, high-contrast color like blue or purple and use a warm, low-contrast on the other end. This will accentuate the dark-to-light transition. Moving in the opposite direction fights against this natural trend—it will be more difficult to read and it won’t look very good.

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