Whether it’s for websites, graphics etc., choosing the colour scheme is a challenge in itself. The choice of colours sets the mood for the things you create. It’s true for data visualization, as well.
In data visualization, colour is crucial to convey the information to your audience. Colours can make a great difference; it can give life to your visualization or break it. The colour scheme you choose sets the tone of visualization and each colour you use to present a different piece of information. The colour palette selected carefully helps in harnessing the pre-attentive processing ability of the human brain making easier to understand the information and visualization more effectively.
There are certain things that you need to know well before choosing colours for your data visualization. Let’s find out the necessary things:
Is your data qualitative, sequential or diverging?
You should understand well the data you’re using for data visualization before choosing the colour scheme. When choosing colour schemes, there are three main categories to be taken into consideration—qualitative, sequential and diverging.
To highlight the qualitative categories, qualitative colour schemes are used. As qualitative data are used to create contrast, different hues can be used to represent each data points.
To organize quantitative data from high to low, sequential colour schemes are used represented by gradient effect. When you use a gradient-based colour scheme, you can present the progression keeping no scope for confusion.
To highlight the middle range and extreme ranges of quantitative data, you can use diverging colour schemes. Two contrasting hues can be used for highlighting the extremes and a light hue can be used to highlight the middle portion.
How many unique hues will you require?
Once you know the kind of display you’ll use in visualizing your data, you have to make out how many hues you will require. The unique hues are the colours such as blue or red in their purest form without any shading or tinting. As creating contrast is crucial in data visualization, unique hues will help in achieving it. When you use contrasting colours, it means the data points are categorical. You can use both qualitative as well as sequential colour scheme in a single visualization.
Role of brightness while selecting colours
When creating data visualizations, it’s very important to consider shading and brightness. If you’re not pointing out the significance of one certain data point in the case of quantitative data, you can use contrasting colours with equally bright hues. In case of sequential quantitative data gradient are likely to be used, shading becomes important.
With various colour tools and premade colour schemes easily available, finding the right colours don’t turn to be the too difficult part, knowing how to use those colours to convey the information at its best is actually the hardest part.