Hexbin Charts: A Better Way to Show Clustered Data in Tableau

Hexbin charts are a type of chart in Tableau that are used to display data that is too dense or has too many data points to be effectively visualized in a traditional scatterplot. They do this by dividing the data into a grid of hexagonal bins and color coding the bins based on the number of data points that fall within each bin.

Tableau Hexbin charts are a type of visualization that is used to display the density of data points in a scatter plot. They are similar to scatter plots, but instead of showing individual data points, they group data points into hexagons and use color to represent the density of data points in each hexagon.

To create a Hexbin chart in Tableau, you will first need to connect to your data source and drag the measures that you want to use for the x-axis and y-axis to the Columns and Rows shelves respectively. Then, you can right-click on one of the measures in the view and select “Hexbin” option to change the mark type to Hexbin.

Some of the key features of Tableau Hexbin charts include:

• They can be used to display the density of data points in a scatter plot.
• They group data points into hexagons and use color to represent the density of data points in each hexagon.
• They can be used to identify patterns in the data that might not be immediately obvious in a scatter plot.
• They can be used to display data in a summarized format.

To create a hexbin chart in Tableau, follow these steps:

1. Open Tableau and connect to the data you want to use.
2. Drag and drop the measure you want to use for the x-axis onto the Columns field in the Marks card.
3. Drag and drop the measure you want to use for the y-axis onto the Rows field in the Marks card.
4. Select the hexbin chart option from the Show Me panel.
5. Customize the appearance of the chart by adjusting the marks, labels, and other chart options as needed.

Hexbin charts are useful for visualizing data with a large number of data points and can help you see patterns and trends that might not be apparent in other types of charts. They can also be used to compare the density of different areas of the data.