1/12 Men & 1/200 Women are colourblind. Meaning, you’ll likely encounter someone and display a data visualisation to someone who is colourblind.

When designing a data viz, how can we create a clear visualisation that both colourblind & non-colourblind people can see?

Colour Blind Number Test

Before going into what practices and rules we can use to help address colourblindness in our visualisations, it’s helpful to understand what sort of colours people may have trouble seeing, and how rare or common these weaknesses are.

There are 8 types of colourblindness:

  1. Red-weak
  2. Green-weak
  3. Blue-weak
  4. Red-blind
  5. Green-blind
  6. Blue-blind
  7. Monochromacy
  8. Blue Cone Monochromacy

Of these, red/green colourblindness are the most common types, with blue and monochromacy colourblindness being rarer. Therefore, I’ll be focusing on red & green colourblindness in this post, but the thought process will still apply.

So how can we design a viz that highlights and emphasises information while taking into account colourblindness?

Selecting a friendly colour palette

The most obvious thing is picking a colour palette that is friendly to the colourblind. There are some common palettes that are used, like:
– Blue/Orange
– Blue/Brown
– Orange/Purple
– Green/Blue
– Yellow/Pink
A good way to check how your colour palette is perceived by someone with colourblindness is through some websites like this colour blindness simulator or this colour filter. David Nichols also has a great article with a colour picker that will show how different types of colour blindness see your combination. That can be found here.

Focusing on colour intensity

Another way to highlight and emphasise data is through increasing and decreasing colour intensity. An example of this is a heatmap.Heat map of sales data
Something to watch out for when doing this is if using more than one colour, such as the profit column. In that case, ensuring you use a colour blind friendly palette is still important.

If you must use red/green, offer alternative pre-attentive attributes

Ideally you will be able to pick a palette that is colourblind friendly. However, if you are unable to or to supplement the colour, consider offering alternative pre-attentive attributes. Size, position and shape are examples of other ways you can draw attention to points of the story you are trying to tell in your viz.

Following these guidelines, you should be able to reach your colourblind audience, and all charts or KPIs you are using to tell your story should now stand out.

The Data School
Author: The Data School