Treemaps

Treemaps are commonly found on data dashboards. Designers often choose them to add visual variety on a dense dashboard. However, treemaps are a complex visualization and present many obstacles to quick comprehension (which is the main requirement for any information displayed on a dashboard).

Creating a tree map involves choosing two dimensions of the data, color-coding one dimension and defining a "tiling algorithm" for the dimension represented by area. The tiling algorithm determines how the rectangles are sub-divided into rectangles of specific area (corresponding to the data). Tree maps are most legible when the area of sub-rectangles have an aspect ratio close to one.

Treemaps rely on area (and possibly color) to encode the value of a variable, and therefore, although treemaps can convey overall relationships in a large data set, they are not suited for tasks involving precise comparisons. Treemaps also should not be used if the data is not hierarchical.


3 Example of "good" treemaps

Treemap corresponding to the tree structure of the S&P 500 dataset depicted above. The color of each rectangle shows if the value of that stock is moving up or down – very bright red indicates a big shift downward, and very bright green indicates a big shift upwards.The size of each rectangle represents the market capitalization (value) of that stock, industry, or sector.
Treemap visualization showing "Elderly population in Europe for NUTS2 regions". Colored rectangles represent the ratio of elderly people ("age group 65 and above") population. The size of each rectangle in the Treemap represents the "Total Population".
Treemap exploring income comparison from films by studio and genre

3 Examples of "bad" treemaps

Treemap depicting someone's personal taste on albums. The sizes of each sector are very similar, not enough visual hierarchy is presented in the graph. The colors tend to blend together, creating more confusion.
Treemap visualization showing "Elderly population in Europe for NUTS2 regions". Lack of hierarchy.
Visually overwhelming 

Source: 1. https://www.nngroup.com/articles/treemaps/

2. https://ncva.itn.liu.se/?l=en

3. https://ncva.itn.liu.se/education-geovisual-analytics/treemap?l=en

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