PUBLISHED ON
Spider charts, or as some know them; radar, polar, web or star charts, are visually compelling and highly effective at visualizing multivariate data for one or more dimensions. However, they’re also often confusing to the untrained eye. Let’s take a look at a simple example to understand how to interpret this chart type:
In the chart above we are comparing two products across five different consumer satisfaction categories. Each spoke of the spider chart represents a different variable. In this case we want to see how the popular iPhone 7 and Samsung Galaxy s8 compare across key buying points, including: design, price, camera, processor, and display.
The same chart can be adopted to visualize data in multiple scenarios, for example: employee performance, sport statistics, sentiment, marketing channel success, etc. Additionally, lines can be replaced with area or column visualizations where preferred. Be mindful when doing so though, as these visualization types occupy more space and may make it harder to decipher your data points if there are multiple dimensions represented on the same graph.
To keep spider charts as readable as possible, limit charts to no more than 3 dimensions and 10 variables. Any more than that, and the visualization may become too crowded or confusing to properly interpret (like the one above).
Be sure to consider who your audience is and question whether alternative graphs would be able to better visualize your data. If there is a simple option that is easier to comprehend, you should always opt for it. Afterall, we want data visualizations to communicate insights quickly and efficiently – there’s no need to overcomplicate them!
Spider charts are sometimes criticized for being difficult to interpret when it comes to effectively comparing values across variables due to their obscure shape. In these circumstances, a bar chart could certainly provide more clarity as the variables are arranged along a single axis. However, it may be more difficult to spot outliers or the overall commonality so make sure to choose your visualization type wisely according to each specific case you face.
Would you like to get more practical tips on data visualization? Download our guide!
Not Another Dashboard.
Add a comment