Color and accuracy matter for effective data visualizations


Communicating data is difficult. Data can complicated and hard to visualize. The way the human brain visualizes images can be used to organize data so it is easy to understand. These simple tips can help you effectively communicate your data to as many people as possible.

Color matters. The human brain craves contrast. When creating a pie chart or bar graph to illustrate your data, using high contrast colors, such as orange and blue, can help your audience easily distinguish data. Color can also be used to create a relationship or invoke emotion. Red makes people excited, while blue is calming. Make sure the colors in the chart are accessible and color-blind friendly. Red-green color blindness is the most common, so avoid using those colors together.

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This alcohol poisoning chart is an example of confusing color usage. The dark-red color is used on both graphs but the information doesn’t relate. Someone glancing at this chart might assume the data is related because the color is the same. (emaze.com)

Use the right format. Continuously ask yourself if the format you’re using to communicate your data is the most effective. If a pie chart has more than seven slices, maybe a table would be better.

Keep your data visualization accurate and honest. Check pie charts to make sure they add up to 100%. Use accurate spacing in line charts. Time can easily be distorted by uneven spacing, making it look like a jump in data is more significant than reality. Keep comparisons minimal. If there are too many comparisons in a bar graph, it can become confusing. Following these rules can also make sure the integrity of your data is preserved.

syrup-related-crimes-2002-2011-2012-some-startling-statistics-5987918
This bar graph tracking syrup related crimes is humorous, but it illustrates an important point. Unevenly spaced x and y axis data can skew the appearance of data changes or increases. (onsizzle.com)

Simple is best. Complicated data visualizations might look important and pretty, but if the reader looks at your data visualization and can’t figure out what it’s saying then what’s the point? Avoid using excess graphic or illustrations that don’t add anything. When in doubt, keep it simple! Data is easier to understand with less details.

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What is this chart saying? Keep it simple, don’t overcomplicate your data. (wired.com)

 

Feature image from martechtoday.com.


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