The Importance of Colour in Data Design

Let’s talk about colour.

How important are colours in data visualisation design? A science and art unto itself, colours play a major part in how information is being conveyed and received by the human brain. Study shows that colour, as part of the electromagnetic spectrum, is in its purest form a wavelength energy with its own magnetic frequency. This frequency thus creates biochemical responses in the brain. Sounds crazy, hey? How fascinating is science!

From the point of view of art and design, the wrong choice of colours can make or break the design. Why? It’s because colours speaks volumes on their own, without needing any words. Each colour represents something — a deeper meaning, if you will, that is understood by the human psyche as soon as the wavelengths transmitted are reflected back to our eyes.

Colour Meanings

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The meanings of colours could either be an emotion or a concept, and were built through years and years of colour association. There’s a lot more to it though! The diagram above represents the most common colour associations in the West. Some colours are perceived completely different through the lens of different cultures.

Take the colour red, for instance. In China, red is associated with prosperity, happiness and good luck, which is why red decorations and clothings are adorned all-over during Chinese New Year. In Africa, red has become the colour associated with AIDS awareness due to the popularity of the RED Campaign.

There are also the factors of hue (think shade) of said colour and how it is used in contrast to other colours. A slight change in hue may evoke different emotions in the viewer or result in different colour meaning. High contrast between two colours create a shockingeffect, whereas the eyes will dart to the more dominant colour. For illustration purposes, let’s look at some examples below…


In this iconic artwork, Barbara Kruger uses a vibrant red in contrast to monochromatic colours to draw attention to the copy printed in red.

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Startup Lab utilises a muted red to evoke energy without being too aggressive.

Knowing the unspoken meaning and the effects of colours on the majority of people is an incredibly valuable knowledge that designers can master and offer to clients. Back to the topic of dataviz design, colour is super important for various reasons:

  1. Due to the ‘pre-attentive’ attributes of data visualisation (meaning: first impressions matter) , choice of colour affects how the audience can grasp the differences in data at first glance.
  2. Data viz is about communicating information through the positioning/size/shape/transparency of objects — the colours of the objects affect how the audience perceives these traits.
  3. Good to note that colour in data viz is about both contrast and hue. But one must address contrast first before worrying about hue. Remember, contrast is about the differences in two colours, and hue represents the colour itself and the shade it is in. But do we know what colours are good next to each other? To have a good insight to this, we have to understand basic colour combinations

Combining Colours 

Colour combination is crucial in creating designs that are aesthetically pleasing to the eye. To have a comprehensive understanding of colours, let’s look at the colour wheel.


Looking at the colour wheel, warm colours are the reds, oranges, and yellows. Opposite are the cool colours — the greens, blues and violets. The colour wheel is an ample guide to create colour combinations that are in harmony to each other. There are several colour combinations that data viz designers can refer to, depending on the outcome that is desired.

1. Complementary Colours


Complementary colour combinations are two colours that sit opposite each other on the colour wheel.

2. Split Complementary Colours


For a combination of three colours, split complementary colours contain two nearing colour hues and one that is opposite of them in the colour wheel, illustrated by the picture above.

3. Triads and Tetradic Colour Combinations


Triads and tetradic colour combinations are three/four colours opposite each other determined through geometric shapes.

4. Analogous Colours


Analogous colour combinations takes colours that are next to each other on the colour wheel.

5. Monochromatic Colours


Monochromatic colours are colour combinations of the same hue, but containing different tints, tones, and shades.

Despite all this information, there is still a lot more to colours. It is truly a vast and subjective topic, one that some build entire careers on, as colour consultants or brand consultants. In terms of data visualisation, the correct colour combo chosen plays a crucial role in the way viewers will digest the data.

If you are struggling to contain all this info, don’t fret! There are various free tools that generates colour schemes to get you started before doing it on your own.


So there you have it, a primer on colours. If you enjoyed this blogpost, then you shall enjoy the Design Principles series that we have cookin’! Keep your eyes peeled for our next one.

Meanwhile, check out some previous posts we have on design:


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Datalabs is a data design agency, specialising in visual strategy, consulting, training, analytics and software development.
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