In our Data Visualization 101 series, we cover each chart type to help you sharpen your data visualization skills.
For a general data refresher, start here.
So far in our series, we’ve dealt with tools for clearly displaying two dimensions of data, but what happens when you have a third or fourth? Do you use a bar chart and stack bars with different variables next to one another? Do you use multiple graphs and compare the results?
Welcome to the bubble chart. This incredibly versatile chart form can be used to visualize a data set with two to four dimensions, all in one elegant and easy to interpret chart.
What It Is
In its most basic form, the bubble chart communicates two dimensions of data: one, a numerical value visualized in the scale of its circular bubbles, and the second in what each bubble represents. Simply put, larger bubbles equal larger values.
Remember the ultra-useful scatter plot? Well, the bubble chart adds even more functionality to that chart form. Combining different-sized bubbles with the x and y axis plotting on a standard scatter plot provides a third dimension of data that can be incredibly valuable. These charts are often referred to as “bubble plots.”
The fourth dimension of data is illustrated in the chart below. By employing different colors to sort data into categories (or even shaded hues across a gradient to represent numbers), the bubble plot reveals its extremely useful nature:
Another popular way to use the elements of a bubble chart is with a bubble map (sometimes called a cartogram). Here, x and y values are effectively latitude and longitude coordinates representing a geographic location (although if locational accuracy isn’t paramount, boundaries like state outlines identify bubbles perfectly).Where It Came From
Like its cousin the scatter plot, the origins of the bubble chart are unknown. The bubble map, however, was successfully used by French civil engineer Charles Joseph Minard (1781-1870). Although it’s questionable whether he was the first to use them, his bubble maps are nearly identical to examples you would find today (minus that romantic yellowing from age). Minard even created what could have been the first combination of bubble maps and pie charts in his map of the cattle trade around France.
In Minard’s “Figurative and approximate map of the tonnage of the major ports and principal rivers of europe” from 1859, we see the fully expressed form of the bubble map. (And because Minard was a master of his craft, each millimeter of river thickness also represents 100,000 tons of shipping):
When to Use It
We called the scatter plot a “discovery tool,” but the bubble chart takes it it to the next level. Here are examples of ways to use each variation:
Two Data Sets
These bubble charts are beautifully simple. In this case, the area of each bubble represents the percentage of personal social networks, while the legend represents the age range for those individuals. (These charts are often used as an aesthetically pleasing alternative to a bar chart.)
Three Data Sets
The bubble plot below combines the usefulness of the standard scatter plot with the additional data provided by varying bubble sizes. Here, we can see a clear correlation between greater ad spending and sales as the year progressed:
Four Data Sets
Adding a legend to differentiate each bubble puts all four data sets together. One of the most famous recent examples of bubble plots was featured in Swedish researcher Hans Rosling’s exceptionally entertaining TED Talk. His “GapMinder” website includes an interactive bubble plot that compares life expectancy in the world’s countries with their income per capita and total population for the last 200 years. Moving the interactive year slider brings the story to life, clearly revealing world changing events like the Spanish Flu pandemic of 1918 and the growth of global trade. This is true chart mastery:
Best Practices for Designing Bubble Charts
Ready to create some bubble charts? Here are 3 tips for how to communicate the most information with a quick glance. (You can also review our tips for scatter plots, which apply too.)
1) Make Sure Labels Are Visible
All labels should be unobstructed and easily identified with the corresponding bubble.
2) Size Bubbles Appropriately
The human visual system naturally experiences a disk’s size in terms of its area. Thus bubbles should be scaled according to area, not diameter.
3) Don’t Use Odd Shapes
Avoid adding too much detail or using shapes that are not entirely circular; this can lead to inaccuracies.
This post originally appeared on Visage.
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