When deciding how to best represent a dataset, a number of questions may pass through your mind. First and foremost: should you represent your data numerically or visually? In this post we’d like to show you why this shouldn’t be such a difficult question, because visualizing how your dataset is behaving can be more powerful and convincing to your most influential decision makers.
One visualization which may not be as familiar as the bar graph or pie chart, but is capable of making a big impact in data reports, is the bubble chart. The bubble chart is a variation of the scatter plot, but it allows for more than 2 variables to be represented at one time. Just like the scatter plot, we can still plot indicators on two axes, but we are also able to show a third variable by adjusting the size of the bubble. In the graph below you can see how a scatter plot can be transformed into a bubble chart by adding a third variable:
|When to use a bubble chart||When NOT to use a bubble chart|
|Bubble charts are best used to:
||Bubble charts are generally not our best option when:
Traditional bubble charts: are used to represent three different dimensions of data in a series, with the area of the bubble corresponding to the value. They have become a popular chart option because they are easy to interpret and allow us to make critical associations between measures.
Multi-series bubble charts:
Allow for more than one data set to be visualized, and also permit the reader to see how the two sets relate to one another.
Table bubble charts:
Tables are typically used to explore specific values across multiple metrics, but you can add visual aids such as bubbles to stress the different values on the table. This allows you to get the best of both worlds! It’s a great visualization for those who prefer to see numerical values. But by following the idea behind bubble charts, and overlaying these bubbles over numerical values, you can emphasize the most important values. This table allows readers to easily distinguish between the values, by drawing the reader’s eye to highest or lowest performing indicators.
So, how do you know which visualization is best for representing your data needs? In reality, this depends on what you’re trying to show, and who you would like to show it to. Both options are strong, but may be suited for different audiences.
If your audience is not well versed in the world of data visualization, the table chart is great option. It’s easy to understand with little to no prior knowledge, and it aids the reader to spot the values that matter most to them. It also makes it easier to distinguish between specific values when numerical values are clustered close together.
The bubble chart may be better suited for an audience who would like to see the data laid out in a chart that lets them see the relationship visually, without focusing as heavily on just the numerical values. Data values may be quite distinct and easy to comprehend without the need for specific numerical values, or the data consumer may purely be looking for patterns.
Categorize and label:
Color-coding bubbles further categorizes them, and adds clarification for the reader. In addition, it may be helpful to accurately label your chart. You may directly label the bubbles, or choose to use a legend. Just be sure that your color choices and labels add to the readability of the graph, in order to allow the reader to find insights without any confusion.
In order to allow your reader to clearly interpret your bubble chart, be sure to also choose a color scheme that will allow for the bubbles to be clearly seen and understood. As you’ve probably already noticed bubbles overlap sometimes, and that’s ok, but you should improve the readability of your graph by using colors that allow the reader to distinguish easily between bubbles. Otherwise potential insights may go unseen if the graph is unclear.
Mean lines: are an additional option available to enhance the classification of your bubbles. They give your reader the opportunity to understand how each bubble relates to the means of the chart, in order to compare how each variable is performing.
Range: If the range of values is too small or the frequency is off, bubble charts can become extremely difficult to interpret. If the reader has to squint just to read the bubbles, the chart has already lost some effectiveness. In the case of an uninterpretable range, try using the bubble table chart instead.
One problem that may arise is when the bubbles all look about the same size, or show little variation. This can be especially problematic in bubble chart tables. In the table below, there is very little variation between the size of the bubbles, which forces the reader to spend time reading through the numbers to figure out just how each indicator is performing. In this case the third variable might be better represented on a separate graph.
Table charts are the most effective when the bubbles allow important information to pop out, making it easy and quick for viewers to find the information most relevant to their reporting needs. The chart below is a great example, of how bubbles make indicators stand out above the rest, in order to allow actionable insights to be taken from them. The reader can easily identify which keywords are performing the best, and which keywords need to be revised.
The addition of the bubble to a traditional scatter plot, or table, adds a powerful punch to the data delivery experience. Bubble charts are an effective visualization tool for quickly spotting comparisons, which permits users to create attractive charts to report their most valuable information to stakeholders.
How do you use bubble charts to create an awesome data delivery experience?
Not Another Dashboard.