Web tool for guidance in choosing choropleth map color schemes, based on the research of Dr. Cynthia Brewer. Built and maintained by Axis Maps.
projects.susielu.com/viz-palette
Create and test pallets for your visualizations on pre-existing data visualizations.
Mathematicly calculated colour palettes.
Colorpicker for Data is built off Gregor Aisch's article How To Avoid Equidistant HSV Colors and the color conversion library chroma.js.
Try not to use colour as the only distinguishing characteristic for identifying data chunks. But if you do, and generally, try to follow these best practices.
Don't use unnecessary colour. In this example, the x-axis already labels the categories (a,b,c,d), so differentiating by colour is not needed.
Avoid using too many colours, people can become confused and overwhelmed. Some sources say no more than 6, some say no more than 10, in one visualization.
Top = sequential data (e.g. 1, 2, 3, 4, 5). Change the intensity of a hue.
Middle = categories (e.g. math, science, languages, etc.). Use colours with distinctly different names.
Bottom = diverging (e.g. -2 °c, -1 °c, 0 °c, 1 °c, 2 °c ). Use 2 hues with different names that merge in the middle.
Always consider cultural implication of colour (e.g. green= good and red=bad, blue=cold and red=hot, etc.)
Some colour combinations are hard for people with colour blindness to distinguish. Avoid these colour combinations: green-red, green-brown, blue-purple, green-blue, light green- yellow, blue-gray, green-gray, and green-black
Ask us