What Is a Treemap?

Key takeaways

Treemaps display data visually, making patterns and inconsistencies easier to see, helping you compare categories and draw conclusions.

• Treemaps rely on clean, well‑structured data, so preparing branches, leaves, and numerical values upfront directly improves the clarity and accuracy of the final visualization

• Treemaps are straightforward to build once you have the right software and a basic grasp of data visualization. You can create them in tools like Tableau, Power BI, Microsoft Word, or Excel.

• You can use treemaps across industries to quickly visualize large, hierarchical data sets when other chart types become cluttered or less effective.

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What is a treemap?

Treemaps represent hierarchical data using rectangles that vary in size and color. Each rectangle represents a category within the hierarchy, or “tree.” Invented by Ben Shneiderman in 1990, treemaps make excellent use of small spaces to translate large amounts of data and are an effective way of viewing data to spot patterns.

Data analysts create treemaps by using computer programs and algorithms. You read them by looking at the sizes of the various rectangles and their relationships. Different colors represent different things, and you can use them in any way that works for you. For example, you may use dark colors to represent extremes, or you may use a continuous color palette to show how profit gradually increased over a fiscal year after the implementation of a new advertising campaign, indicating its effectiveness.

For more complex data, you can nest boxes together to form categories of data. For example, you can create a treemap for each of the departments within your organization. You can use the branch of each treemap to represent the given department and use rectangles under the branch as the leaves to depict the sales information for that department’s various items. 

Read more: Which Data Analytics Professional Certificate Is Best For You? Google vs. IBM vs. Meta

What is a treemap used for?

Treemaps are very versatile. You can use them across multiple industries to quickly create an effective visualization of large amounts of complex data, which may not be possible with other charts and diagrams. If your data is hierarchical, with distinct numerical values, and you’re looking to display only positive values, you can create a treemap.

Some examples of applications of treemaps across industries include:

• Health care: Health care organizations can use treemapping to present large volumes of hierarchical medical data so that stakeholders can quickly see a visualization of complex data, such as vaccination rates among various age groups.

• Business: Businesses can use treemaps to collate and present business data, sales data across industries, or profits per employee.

• Politics: Politicians and election teams can use treemaps to display political data, such as how well one party or candidate is doing against another before an election.

• Research: Researchers can use treemaps to compare study participants’ demographic information and look for trends and patterns.

• Finance: Investors and finance professionals can use treemapping for portfolio management to analyze investment allocations and portfolio diversification.

Pros and cons of treemaps

Treemaps are effective visualization tools that you can use in a range of industries to represent all kinds of hierarchical data. This tool comes with advantages over other methods, but as with anything, it also comes with limitations.

Advantages

Treemaps make it easy to view and compare data:

• Small space: You can use a treemap to efficiently utilize space in a report, visualizing large data sets compactly.

• Hierarchical design: You can use the hierarchical design to go as deep as you need to in the data while still operating with a simple visual design, adding as many levels as you need.

• Different sizes: You can break larger categories of data down into smaller categories to help viewers quickly inspect the data and draw conclusions, such as that a café sells more cookies than muffins in the afternoon.

• Different colors: You can use different colors for different attributes, such as departments, product types, or subgroups of people. For example, using blue to represent the overarching category of office product sales and incorporating different shades of blue to represent each subcategory, such as copy paper and writing utensils.

Challenges

However, treemaps do have some limitations:

• Cluttered: The treemap’s design means that it can become cluttered when representing large data sets.

• Difficult to read: Treemaps can potentially be difficult to read because they contain large numbers of rectangles (leaves) at multiple levels (branches).

• Difficult to interpret: Treemaps can make it difficult for viewers to interpret the various levels of the hierarchy; effective treemaps have obvious levels of hierarchy and no more than four rectangles.

• Numerous software options: Many tools and software options are available to use to create a treemap, and some are more effective than others, so data analysts must conduct research and choose the option with all the functions they need for their project.

Does Excel have a treemap?

Yes, Excel includes a built-in treemap chart type that displays hierarchical data as nested rectangles, making it useful for visualizing categories and subcategories and comparing their relative sizes. You can insert from Excel’s Insert tab under the hierarchy chart options.

Getting started with treemaps

Treemaps are easy to create with the right software and tools, and a basic understanding of data visualization. You can use Tableau or Power BI software, or make your map in Microsoft Word or Excel.

1. Prepare your data: To create a treemap, select the data you want to use and input it into your data visualization tool. By creating levels of data (branches and leaves), you'll be able to create a hierarchical structure.

2. Assign numerical values: Give a numerical value to each data set to determine the color and size of the rectangles according to your specifications, such as color palettes and filtering.

3. Add labels: Label each rectangle in your map to clearly show what each element represents.

4. Use your treemap: Use your treemap to get to know your data by identifying patterns and inconsistencies and making comparisons.

Explore our free resources for data-driven professionals Join Career Chat on LinkedIn to stay current with the latest trends in your career field. You can also continue your learning journey with data visualization with our other free digital resources:

• Hear from an expert: Reimagining Work and Learning with AI: Expert Insights from Dr. Jules White

• Learn some terminology: Data Analysis Terms & Definitions

• Watch on YouTube: How to Sort and Filter in Excel | Organize Large Datasets Like a Pro

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