Treemaps primarily indicate value through the size of the rectangles they use.
They are made of a series of nested rectangles of sizes proportional to the corresponding data value. This means that the larger the area of a rectangle within the treemap, the greater the value it represents compared to other rectangles in the same hierarchy level.
The Core Mechanism: Size Matters
At its heart, a treemap uses space efficiently to represent data. The fundamental way it shows value is through the area of each individual rectangle.
- Larger Area = Higher Value: A rectangle with a larger area signifies a higher data value or proportion.
- Smaller Area = Lower Value: Conversely, a smaller rectangle represents a lower data value.
This visual encoding allows you to quickly grasp the relative importance or magnitude of different data points or categories by simply comparing the sizes of their corresponding rectangles.
Showing Hierarchy: Nested Rectangles
Beyond just individual value, treemaps excel at showing hierarchical relationships, and they use nesting to do this, which also indicates value within categories.
According to the reference, A large rectangle represents a branch of a data tree, and it is subdivided into smaller rectangles that represent the size of each node within that branch.
- Branches and Nodes: A larger, containing rectangle represents a higher-level category or "branch" in the data hierarchy. Its total area is the sum of the values of all the items within it.
- Subdivision: This large rectangle is then divided into smaller rectangles, each representing a sub-category or individual item ("node") within that branch.
- Value within Hierarchy: The size of these smaller rectangles indicates their value relative to the other items within that specific larger branch. You can see how much each part contributes to the total of its parent category.
Practical Interpretation
Understanding how rectangle size and nesting work together allows for practical insights:
- You can quickly identify the dominant items or categories in your dataset by spotting the largest rectangles.
- You can compare the proportion of one item to another within the same group by looking at their relative areas inside the parent rectangle.
- You can see how value is distributed across different levels of a hierarchy simultaneously.
For example, in a treemap showing market share by product category and then by individual product:
- A large parent rectangle for "Electronics" means electronics have a high overall market share.
- Within "Electronics," a very large smaller rectangle for "Smartphones" indicates smartphones are the dominant product within that category.
- Smaller rectangles for "Tablets" or "Wearables" show their relative contribution to the "Electronics" market share compared to smartphones and each other.
Treemaps effectively translate numerical values into visually comparable areas, making it easy to see proportions and identify significant values, especially in hierarchical data structures.
