# Bubble To learn more about bubble charts and how to create one, please view this [video](https://youtu.be/a3Ca1T41ak8?si=c-B9E4ljnd9GfBcP). 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](/immerse/measures-and-dimensions#dimensions) | 1+ | Minimum 1, no limit, null dimensions optional. | | Required [Measures](/immerse/measures-and-dimensions#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. ### # Of Groups Display up to 100 groups of records. You can enter a value or use the slider to visually set the number of groups. ### Null Dimensions Choose whether to show or hide Null values for your chosen dimension. ### Color Palette You can use a custom palette to visually group values in your chart. By default, data points are colored arbitrarily with a spectrum of solid colors. You can choose to arbitrarily color bubbles with 2, 3, or 4 colors. You can also apply colors to individual Dimension values. If you set the **Color** measure, you can choose a gradient to visually express relative quantitative values. ### Custom Measure Formatting You can use custom measure formats for the values in your chart. See [Customizing Measure and Date Formats](/immerse/measures-and-dimensions#customize-formats). ## 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](http://www.ukcpr.org/data). *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. ![](https://files.buildwithfern.com/heavyai.docs.buildwithfern.com/heavyai/142b5876cc5116c4e15b079c7fc49ca8271b37b6a649e3c6c2f1055454d34806/docs/assets/3_bubble-1.png) 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. ![](https://files.buildwithfern.com/heavyai.docs.buildwithfern.com/heavyai/baf3468b5d6406979c599d2df2053158d1b4167eeeb9b48842127293ca0e7629/docs/assets/3_bubble-2.png) You can add *Employment* as the **Color** measure, which casts California in a more favorable light. ![](https://files.buildwithfern.com/heavyai.docs.buildwithfern.com/heavyai/b478f2c89603bb352eabf05516ead6a29e61c793505f51d4d12d918e07b02261/docs/assets/3_bubble-3-2-2-2-1-8-1.png)