Data Cruise

Data visualisation is a key aspect of the data analysis process. It is extensively used during the data exploration stage when analysing data and likewise useful as an explanatory tool to convey findings at the final stage of the process. However, the purpose of data visualisation may be unrealized if it is not well designed with the appropriate colours.

Colours are important design elements for an apt and interpretable data visualisation. They are important in drawing the eye of our audience to key findings and differences in the data. More so, they are useful for highlighting particular data points, representing categorical data and encoding additional information to quantitative data. However, its application should be done strategically in order to achieve the desired result.

How then should colours be applied to data visualisation?

There are three types of schemes for choosing colours when designing data visualisations. They are:

1. Sequential Schemes: Single colour hue with varying saturation and lightening. The colour graduates from light to darker colours and is good for quantitative data.
2. Divergent Schemes: Different colour hues with the same saturation and lightening. This is good for categorical data as it does not allow each data component to appear better than the other.
3. Qualitative Schemes: The neutral colour is in the middle and it spreads out in two directions. It is also good for classifying categorical data.

Many people make the mistake of using many colours during data visualisation design in order to make them more colourful and consequently get their audiences’ attention. This is actually not a good practice. Wrong colour choice and combination may cause distractions and several misconceptions.

The following are some of the things to consider when applying colours to data visualisation. 

• More than two colours should be avoided unless they convey additional information about the data. A shade of grey alone could just be all that is needed to effectively communicate the message.
• It is always better to avoid bright colours and use the natural pastels instead. This is because people focus more on colours with softer fills and this facilitates communication.  
• They should be tolerable to people with color blindness. The Red and Green colours are adverse colours for individuals with this visual deficiency because they hardly recognize the difference between the two.  

Unlike the aforementioned colours, they can easily identify the difference between the Orange and Blue colours making them more preferable colours for data visualisation.

Conclusion

It’s no doubt that colours are important in data visualisation. However, it is more expedient they are used appropriately in order to prevent the misinterpretation of our data and findings.

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