Making Corporate Color Palettes Palatable

Meagan Longoria takes us through a corporate coloring problem:

Last week, I had a conversation on twitter about dealing with corporate color palettes that don’t work well for data visualization. Usually, this happens because corporate palettes are designed with websites and/or marketing collateral in mind rather than information graphic design. This often results in colors being too bright, dark, or dull to be used together in a report. Sometimes the colors aren’t easily distinguishable from each other. Other times, the colors needed for various situations (main color, ancillary colors, highlight color, error color, KPIs, text, borders) aren’t available in the corporate palette.

You can still stay on brand and create a consistent user experience with a color palette optimized for data visualization. But you may not be using the exact hex values as defined in the corporate palette. I like to say the data viz color palette is “inspired by” the marketing color palette.

Click through for lots of goodies, including a link to a really interesting color tester.

Related Posts

Visualizing with Heatmaps in R

Anisa Dhana shows how you can create a quick heatmap plot in R: To give your own colors use the scale_fill_gradientn function.ggplot(dat, aes(Age, Race)) + geom_raster(aes(fill = BMI)) + scale_fill_gradientn(colours=c("white", "red")) This is a quick example using ggplot2 but there are other heatmap libraries available too.

Read More

The Power of Hexagonal Binning

Capri Granville explains hexagonal binning to us and gives a few examples: The reason for using hexagons is that it is still pretty simple, and when you rotate the chart by 60 degrees (or a multiple of 60 degrees) you still get the same visualization.  For squares, rotations of 60 degrees don’t work, only multiples […]

Read More

Categories

May 2019
MTWTFSS
« Apr Jun »
 12345
6789101112
13141516171819
20212223242526
2728293031