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Touche example11/14/2022 This cookie is set by GDPR Cookie Consent plugin. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". The cookie is used to store the user consent for the cookies in the category "Analytics". These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly. Now go forth, and use colours in your data visualizations wisely.Ĭlaus O. And whenever possible, colour should be used intentionally to communicate a narrative within its given context or layout. The data visualization palette also needs to complement (but not compete with) the brand and UI palettes. To become an expert at data visualization design, the colours within the palette need to work for any given visualization and be accessible to all users. #TOUCHE EXAMPLE HOW TO#If there are multiple charts within the same view, make sure that identical data points across the charts are using the same colour.įor example, if you are comparing this year’s data to last year’s data, make sure that “this year” is always represented by the same colour.ĭesigners pride themselves on being colour experts, but it’s another skill set entirely to understand how to craft colour palettes and successfully apply them to data visualizations. This could cause visual conflict if not designed intentionally. Keep data point colours consistent when there are multiple visualizations in the same layoutĪ product dashboard is an example of where you might include multiple visualizations in the same layout. If, for example, a product layout has the same colour for the brand elements, primary call-to-action, hyperlinks and chart components, then a user could mistakenly assume the data in the visualization is associated with UI components in the same layout. Unfortunately, the well-intentioned consistency can introduce conflict into the overall layout. In the interest of keeping visual elements as consistent as possible, designers often use the exact same colours for their branding, UI and data visualization palettes. If you also include those specific error state colours in your data visualization palette, you might risk the data being misinterpreted.Īvoid sharing colours between your branding, UI and your data visualization palettes So it shouldn’t come as a surprise that UI palettes commonly use the colours red, yellow and green to reflect destructive states, success states, and warning states. Humans typically assign the colour red with negative connotations, green with positive ones and, if necessary, yellow is introduced as an intermediary colour. Traffic lights across the world leverage the same three colours: red, yellow (or orange) and green. Take, for example, the design of a traffic light: An example use case might be using colour to highlight a specific category for comparison.īe aware of human associations with colours, and use them to your advantageĮveryone perceives colour a little bit differently, but there are known human psychological associations with specific colours based on what we see in the world around us. Colour can, and should, be used to intentionally communicate that narrative for the user. Only use a categorical colour palette in charts where categories require colour distinction.ĭata visualization design will often have some level of persuasion or narrative involved, depending on the context. Using too much unnecessary colour will distract the user from the data itself. Just because you have access to a range of colours in your palette doesn’t mean you should always use them all. Less is more: be intentional about the colours chosen to communicate the overall data story Depending on the context, this can be detrimental to important business decisions.īelow are some examples of unsuccessful data visualization colours and tips on how to improve them. If colours are not applied intentionally, the outcome can result in the misinterpretation of your data. Now that you have an understanding of how to select colours and build data visualization palettes, it’s time to apply them to visualizations themselves. In part 2 we will discuss how to design successful data visualizations, but but before we do, read part one. But it’s a delicate balance ensuring that those stimulating visualizations are still doing their core job: communicating the data successfully to the user, in the given context. But working with colour becomes more challenging when the product you’re designing is a data visualization platform.Ĭolourful data visualizations can provide visual excitement in an otherwise traditional user interface. As designers, one of the primary techniques we pride ourselves in mastering is crafting colour palettes for our clients’ products.
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