# Bubble Chart: Types of Bubble Plots

Descriptive Statistics > Bubble Chart

## What is a Bubble Chart?

Bubble plot showing Medicare amounts per service/specialty. Image: CMS.gov.

A bubble chart is a way to show how variables relate to each other. It is similar to a scatter chart, only instead of dots there are different sized bubbles.

Bubble charts are a good choice if your data has 3 series/characteristics with an associated value; in other words, you need:

• a category with values for your x-axis,
• a category with values for your y-axis, and
• a category with values for sizing your bubbles.

They are often used for financial purposes and for use with quadrants.

## Types of Bubble Chart

In its most basic form, larger bubbles indicate larger values. The placement of the bubble on the x-axis and y-axis give you information about what the bubble represents. This chart shows length of investment (x-axis), price at time of purchase (y-axis) and the relative size of the investment today.

Color coded bubble plots use color to sort the bubbles into categories. For example, I might want to sort my investment chart into stocks, bonds, and mutual funds:

A cartogram is a bubble plot of a map, where the x-axis and y-axis are longitude and latitude. The size of the bubble could indicate population, number of oil rigs, natural weather events, or some other type of geographical data.

The charts are sometimes referred to by dimensions:

• Two-dimensional charts have x-values and y-values only. They are equivalent to a scatter plot.
• Three-dimensional charts have the x-y axes and bubble size.
• Four-dimensional charts have x-y axes, bubble size and color.

## MATLAB Instructions

Use the SCATTER(X,Y,S,C) command.

• Vectors X and Y must be the same size.
• S is the area of each bubble (in squared points). S can be a vector or a scalar. If scalar, all markers will be the same size.
• C is the maker color.

If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.