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How To Get Colours Working For Your Data

link to original storyFeb 27, 2017
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Just like all other situations where choosing colours, aesthetic factor is important. However, as colour has clear roles to play when they are painted to data, I would argue that functional factor comes as priority. In data display, because what it encodes is data, use of colours need to be done with care. Without great care, you could end up with creating charts that confuse or even mislead readers. It also means that deliberate choice of colour can effectively strengthen the message that you’re trying to convey through your visualisation. Good understanding of its functions and basic rules attached is necessary to use colours to effectively communicate with data. This post discusses 4 key functions and associated rules.

1. Colours set the context for primary information

A piece of data visualisation consists of various visual elements which can be categorised into either of two kinds; data and non-data (or primary and secondary). Bars in the bar chart, lines in the line chart and dots in the scatter chart are data/ primary elements. Meanwhile, elements such as grids, labels, and axes are contextual elements that ‘set the stage’ for the data points — the main ‘actors’. In this sense the non-data elements are also called contextual elements. The best practise is to use unobtrusive yet still legible colours such as light grey for the non-data elements, to avoid distracting the focus from the data. As can be seen in Figure 1 below, ‘silencing’ the contextual elements makes the chart on the right much clearer.



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