Image -> 1000 words… Colors -> more than it
When working on data visualization, dashboards get lit up with color like Christmas tree. Every color has a meaning associated with it. Colors can draw our eyes to what is important and binds the similar things. Example, similar characteristics are represented with same color but different hues when working on dashboard. Why so ? because same color hue can help remember the things which are connected.
The problem with colors is they are dependant upon the context which is being used. For example, Red is used to represent love, desire and excitement… but also it can be used to showcase danger/alarm.
There are certain guidelines we need to follow while choosing colors for data visualization. They are:
- Shades of same color showing ordered data (From low to high).
- Divergent when dealing with ordered values and it has midpoint.
- Categorical when data falls into groups..rainbow colors.
Consider and example of spending app where you want to show alerts based on user limits. So, the color scheme here would be to show alert in red when overspending… yellow when spendings are high… and green otherwise. While designing dashboards, a common rule for three-color palette in design is 60-30-10 rule. To explain it, 60% for the color account for dominant hue in design while rest two colors contribute remaining view. To simply put, consider man’s business suit attire where suit and jacket account for 60% of color in the outfit, while the shirt accounts for 30% and tie color at 10%.
It is being observed that red-green colors are most common but it should not be used heavily to convey meanings. Showing indicators like arrows to indicate data flow should be eye-catchy. Also, maintaining consistency throughout design is important factor. For example, if black color line is used to show trend.. it should be used wherever we are showcasing trend. Also, desaturated colors are preferred more professionally than bright/bold colors which can be seen childish.
To end, the reason we follow these guidelines is to make our dashboard more informative, more easier to understand.
By Gaurav Chavan