# Bubble Chart

A Bubble chart is a variation of the Scatter Plot. Aggregated data is grouped by dimension into circles displayed on an x/y axis. Additional measures change the size or color of the circles. A Bubble chart can represent up to four measures for your chosen dimensions (x, y, size, and color).

Features | Quantity | Notes |
---|---|---|

Required Dimensions | 1+ | Minimum 1, no limit, null dimensions optional. |

Required Measures | 2-4 | Measure 1 = x axis, Measure 2 = y axis, Measure 3 = bubble size, Measure 4 = bubble color. |

Use a Bubble chart to show a correlation between the x measure and the y measure. When you do not expect a correlation, you can use a Bubble chart to understand the distribution and influence of multiple factors.

## Bubble Chart Examples

Create a new Bubble chart. Choose a **Data Source**. This example graphs employment statistics for all 50 United States for the years 1980-2015. The data is available at the University of Kentucky website.

*State_name* is a handy dimension for this data. Use the average *Unemployment_rate* as the **X Axis**, and the average **Unemployment** total for the **Y Axis**. Increase the **# of Groups** to 50 to create an individual bubble for each state.

California has a significantly higher number of unemployed residents compared with the other states. Bubble charts are a good way to show outliers in a dataset. But that figure might be misleading. One reason for a higher average number of unemployed persons might be the fact that California is the most populous state in the country. Use *Population* as the **Size** measure to create proportionally sized bubbles, based on total population.

You can add *Employment* as the **Color** measure, which casts California in a more favorable light.