For a video tutorial on creating a treemap in Microsoft Excel, scroll to the end of the written tutorial.
A Brief History of Treemap Charts
Treemap charts are a form of area-based visualization developed in the early 1990s by Professor Ben Shneiderman at the University of Maryland Human-Computer Interaction Lab. While area-based visualization diagrams like mosaic plots have existed for decades, Shneiderman sought an efficient way to display hierarchical data visually. He was seeking a less “bulky” tree-structured nod-link diagram that he was already using.
Purpose of Treemap Charts
Treemap charts help visually identify hierarchical rankings in a flat structure. Their efficient use of space and color management makes them an exceptional instrument in visualizing large amounts of information for business and marketing analytics applications and other industrial uses.
The way treemaps display their hierarchies is through rectangles of varying sizes and colors, depending on the amount of data provided for each part. The combination of colors and different sizes of rectangles (or boxes) makes it easy to see patterns often challenging to spot in other scenarios, like pie charts. Because treemap charts use space efficiently, another advantage of them is that you can display thousands of items simultaneously.
The Treemap’s goal is not to display the exact values of each part but to exhibit the datasets into parts to identify its larger and smaller constituents quickly.
Some Cautions When Using Treemaps to Tell Visual Stories
Like other data visualization charts, treemaps have some precautions to heed before telling their visual story using the datasets. These precautions include:
- Determine if a treemap is the best type of chart to tell your visual story. People are bad at calculating area. Because the Treemap relies on displaying area as its data hierarchy, people may not be able to decode the numerical information by the area. In this case, a pie chart or bar chart may be better suited for your visual story.
- When you have similar numbers, the Treemap generates similar block sizes resulting in difficulty making comparisons on the chart.
- Treemaps can only process positive number datasets. They do not process negative values.
- If you require a common baseline to present your data, treemaps are not advisable. Bar charts are a better approach for this type of visual storytelling.
- Keep in mind that text may appear very small on treemap blocks. Creating a color legend describing each block is advised. If your Treemap is interactive, you should provide a pop-up tooltip over each chart area.
Creating Treemap Charts in Microsoft Excel
Microsoft introduced the treemap chart along with several other data visualization tools in their Microsoft Office 2016 release. The Treemap is available on both the macOS and PC versions of the software.
Treemap Chart Excel Tutorial
Please note that this tutorial uses screenshots from a macOS. Where appropriate, I will include PC commands for PC Microsoft Excel users.
The data I’m using originates from data.world, and the dataset is titled “Social Influence on Shopping.” I will create a visual comparison of which astrological signs and social media platforms influence university students to make online purchases from the data.
To begin, select the dataset you wish to work with, or you can click the Download link to get the sample .csv dataset I’m using for the tutorial.
Select the data you want to visualize.
For Mac: Click the Insert tab on the ribbon, click the Hierarchy icon, and select the Treemap.
For PC Users: Navigate to the Insert tab. Select Insert Hierarchy Chart, then select Treemap.
Your treemap will appear on the same excel sheet as your data. You can add or change the title by directly clicking into the title box within the treemap.
Creating treemaps in excel is simple, as you can see from both the written and video tutorial. Deciding how you want to convey your data story will dictate how you organize and select your data. The treemap chart allows marketers to quickly display a visual representation of the data they choose to tell their story visually.