Bubble Charts

Understanding and Using Bubble Charts

A Bubble chart is a visualization that can be useful in showing high-level comparisons between members of a field. Precision is not the name of the game here as it can be difficult to make visual comparisons when bubbles are close in size or are not placed next to the category or member in question. Instead, bubble charts are effective at giving us directional guidance with regard to our data and how the members within a field compare.

In any bubble chart, the size of the bubbles is a reflection of the values of the categories or members within a field. The number of categories within your selected field will determine the number of bubbles in your chart. You can add color to provide insight and it is often used to help identify categories or as a way to gauge numerical value. For additional interest, bubble charts can have different stylized approaches, including pictures superimposed on each bubble, however clarity of message should always come before style for style’s sake.

You can also use labels to make comparisons easier, and communication more effective. However, some of the bubbles may not be large enough to contain a label. If seeing each value is necessary it may be worth considering an alternative chart. Something like a bar chart doesn't need labels because it communicates without them.

How To Read Packed Bubble Charts

When presented with a bubble chart, the goal is typically to allow you to quickly make a comparison between members of a categorical field. To do so, end-users should visually compare the size of the bubbles as well as the color to the other field members in the view to draw conclusions from the data. Additionally, the end-user can identify the number of categories within your selected field by counting the number of circles appearing in your chart.

Bubble charts should have each bubble labeled for ease of understanding and a linear bubble chart will have light grid lines to allow the reader to see where the bubble is in comparison to the other bubbles on the chart. On linear Bubble Charts, bubbles have the potential to overlap. If they do overlap, due to chronological order or size, labels may not display. In this case, it's worthwhile to use an alternate chart to allow viewers to identify the value of the chart.

What Type of Analysis Does A Bubble Chart Support?

In this view, we can see that Food has the highest number of borrowers with Retail coming in second.

Bubble charts can help to simplify a complex dataset into a visual that makes it easy for viewers to compare members within a given field. For instance, one could analyze which Kiva loan types are the most popular (have the most borrowers) worldwide. Color then categorizes the bubbles by the type of spend they represent.

When and How to Use Bubble Charts for Visual Analysis

A bubble chart can is useful as a way to visualize your data if you have at least one measure and one dimension and you are looking for a compact way to visualize the information. However, bubble charts become less effective if you’re trying to show specific numbers or make exact comparisons as circles are difficult to make exact comparisons between, especially when they are similar in size.

When using a bubble chart:

  • Use few colors and ones that are easy to distinguish
  • Label the bubbles
  • Sort the bubbles by size to make it easier for the viewer

Don’t use a bubble chart if:

  • You only have one mark in a field
  • There are too many bubbles, making analysis difficult.
  • The range of values is very small between marks
  • The position of your marks on an axis is important

Great Examples of Bubble Charts

This bubble chart shows a split in the gender of borrowers from a specific bank. The bubble that represents female borrowers is larger than the bubble that represents male borrowers. These two bubbles correctly represent the portion for male borrowers and female borrowers.

  • Turquoise represents the female borrowers.
  • Gray represents the male borrowers.
  • There are only two bubbles in this graph, making the difference obvious.

This bubble chart shows the number of spacewalks that happened every year between the years 1998 and 2019. Each bubble is proportional to the number of spacewalks and shown in chronological order.

  • The bubbles overlap, showing trends over time. It is obvious that between 2005 and 2011 there were more spacewalks than any other time period. 
  • The bubbles are all one color, leaving the viewer aware that each bubble measures the same dimension
  • The bar chart above shows the data in the same way as it is presented in the bubble chart. However, the relationship between years is not as obvious in the bar chart.

Bad Examples of Bubble Charts and Alternatives


This bubble chart looks at the number of borrowers from the bank based on their country of origin. This chart is too confusing for viewers to gain much useful information about the data.

  • Too many bubbles overwhelm the visualization.
  • The chart is not sorted to group countries by their bubble size.
  • Some of the bubbles are almost too small to see.
  • Some of the colors are too similar for viewers to determine what bubble belongs to what color on the legend.


A better alternative to the bubble chart above is the ever-versatile bar chart. This chart shows the number of borrowers from each country in order from largest to smallest. The numbers are clearly defined on the bars and the viewer is not overwhelmed by the overuse of colors.