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Treemap Chart: What It Is, How It Works, and When You Should Use It


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The treemap chart is a unique graphical representation tool majorly used in visualizing hierarchical and part-to-whole relationships. Rooted in information visualization and graphic design, it presents data in nested rectangles. Each rectangle represents a data point and its size and color represent dimensions or metrics of that data. In this article, we go over what a treemap chart is, how it works, and when you should use it.

The Concept of the Treemap Chart

Essentially, the key advantage of the treemap chart is its capacity to recognize patterns instantly that would be hard to understand from raw data. The chart can encode large amounts of hierarchical data in small spaces without sacrificing the data’s meaning, making it a popular choice for data analysts.

Developed by Ben Shneiderman in the 1990s as part of his research at the University of Maryland, the treemap has found its way into various fields. It is commonly used in finance, stock market analysis, data analysis, and software visualization among others.

From its simplicity to its ability to organize multiple variables in one-dimensional visualization, it’s clear that the treemap chart plays a vital role in data representation. Whether it’s for business analysts or data scientists, understanding what a treemap chart is, and its application is pivotal for sound decision-making.

Breaking Down How Treemap Charts Work

A treemap chart takes a dataset with a hierarchical structure and presents it in compact, space-efficient rectangles. The top-most category on the hierarchy is represented by the outermost rectangle and the subcategories within this are represented by smaller rectangles nested within.

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The size of a rectangle in the treemap chart represents the quantity or measure of the data. If the data point’s measure is large, the respective rectangle will be big, and vice versa. The colors in a treemap chart indicate categories or dimensions, helping users differentiate between data points rapidly.

The chart simplifies data browsing by placing similar data together and contrasting dissimilar data. For instance, if we take a dataset about a tech company’s employees, a treemap chart can present this in a way that instantly shows the departments with the most employees, the respective roles within these departments, and even further. This paints a clear picture of what otherwise would be a muddled maze of raw data.

Suitable Scenarios for Using Treemap Charts

There are several scenarios where a treemap chart is an excellent choice for data visualization. In finance, a treemap chart can be employed to display stocks within a portfolio, with rectangles colored to signify gains and losses, and sizes signifying total market share.

Additionally, in computer science, treemaps can be instrumental in visualizing file structures on a hard drive, with rectangles representing folders and files. In such a scenario, the size of each rectangle can exemplify the size of the files or subfolders within them.

For e-commerce, a treemap can show sales of different products. The rectangles can represent product categories with size showing volume or revenue, and color showing performance. One glance at the chart provides a picture of what product categories are the best performing and which are not.

Overall, with their ability to present complex data in a simplified, comprehension-friendly format, treemap charts are perfect for sectors with a lot of datasets including finance, marketing, human resources, and manufacturing, among others. The suitability of this chart type is wide and varied, making it a versatile tool in the data visualization toolkit.

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Bellie Brown
Bellie Brown
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