You have just made the most aesthetically pleasing pie chart in the history of data viz - but has your color palette inadvertently introduced a bias to the data you're presenting?
Our brains interpret color contextually: proximity to other colors changes the way we perceive a particular color, making it appear darker or lighter, more prominent or more demure. When presenting data visually, it's important to choose color palettes which do not skew the viewer's perception of the data relationships you're illustrating.
In this talk, we'll take a peek at some basic color theory based on the work of Josef Albers, look at what color weight is, and how you can use it to evaluate your palette choices. We'll learn why those gorgeous palettes created by graphic designers may not be the best choices for your data visualizations, and present some strategies for choosing color palettes that keep your data presentation both unbiased and visually pleasing.
This is a tool-agnostic talk: you can apply these techniques with any data visualization package or tool which allows you to specify a color palette.