Like Scatter charts, Bubble charts use circle shapes to represent numeric data but add a third data series that determines the size of the circle. Bubble charts are often used to present financial data. For example, you might see a Bubble chart that represents the age of investment on the X-axis, the return on investment on the Y-axis, and (for the bubble size) the amount of the investment, like this:

For one additional level of information you can color-code the bubble by specifying a "Group By" parameter. In the above example the circles are color-coded by investment type.

As with scatter charts, bubble charts are useful in displaying relationships between numeric values. The addition of the size element to the bubble allows you to compare three values instead of just two - it would take multiple scatter charts to display the same data, and even then you might not see the correlation between all three variables clearly.

See the section Bubble Chart Examples below to see it in action. They highlight situations where Bubble is a great choice to display your multi-variable data sets.

Remember that the size of the bubble is critical when interpreting these charts, so make sure that your data range has significant enough variation to make this chart type a good choice. If this third value is not significant, you may want to take another approach to your data visualization.

Avoid using bubble charts if you don't want to show the relationships between three independent variables, or if the third variable is not important in your analysis - comparing two numeric values is the domain of Scatter charts. You may also consider other chart types if you are not comparing a relatively large number of data points - sparsely populated bubble charts do not give viewers a good sense for correlation in the data. If your data has a periodic component you might want to investigate Bar, Column or Line charts as well.

Configuring a Bubble chart is easy with the SmartSuite Chart Setting panel. Just follow these easy steps:

Bubble Chart Type

Select bubble chart under Chart Settings to get started with your configuration.

The Values configuration section allows you to pick which field or fields contain the data you want to display on your chart. Bubble charts have three configurable Values, one for the X-Axis (horizontal values), one for the Y-Axis (vertical values) and one for Bubble size. All of the numeric type fields in your Table (Number, Currency, formulas that output a number, etc.) are available for selection.

Group By has a special function in Bubble charts - it lets you color code your displayed data points! Simply select the field you want to group by (list-type fields like single select, date fields and more are available) and your data will be identified by the selected value, like this:

Bubble charts are great on their own, but even better on a SmartSuite Dashboard!

All of the configurations are the same as we've described above, with a handful of minor differences:

Once you have configured your chart parameters to your liking, click Add Widget to place it on your Dashboard. That's all there is to it!

Here are a few charting use cases to get you thinking about Bubble chart and when it can be the best chart type choice.

Bubble charts excel at demonstrating the relationship between three numeric values and telling a story at a glance. This visual depiction shows you instantly what brands are driving volume and what percentage they are of overall profit (represented by the size of the circle):

Bubble charts make it easy to sense where data is grouped, showing the user a visual representation of the information that is easily digested. Relationships between three variables may be hard to discern in a bar chart, but are seen at first glance when represented in a bubble chart. As an example, let's look at a data set that represents relationships between COVID-19 hospitalization data points, in this case patient age (X-Axis), Average Hospital Stay (Y-Axis), and total COVID deaths in the population (Circle size).

While you could certainly create other chart types that show you portions of this data, you can see definite patterns and data "clusters" here, making it clear that there is a significant concentration in the mid-seventies age group with an average hospital stay of >3.5 days.