It uses rectangles to display hierarchical data. The color and size dimensions are correlated in some way with the tree structure.
Its advantage is that it simultaneously show the big picture, comparisons of related items, and allow easy navigation to the details. However, it is really hard to get all the rectangles at the correct ratios in correlation to the data.
Each box in a treemap can show two measures:
- Size of the boxes should be a quantity measure. The measures should sum up along the hierarchical structure of the data. The sum of all the elements in one branch need to sum to the value of the branch as a whole. Therefore, you can’t use ratios or dates or any other measure you wouldn’t use in a pie chart.
- Color of the boxes is best suited to a measure of performance or change such as growth over time, average conversion rate, or customer satisfaction.
A rectangle area is proportional to a specific dimension of the data. Often the leaf nodes are colored to show a separate dimension of the data.
3 Good examples: (description underneath the images)
1) Treemap of the 2016 United States presidential election results in Florida by county, on a color spectrum from Democratic blue to Republican red.
2) Treemap of Singapore's exports by product category, 2012. The Product Exports Treemaps are one of the most recent applications of these kind of visualizations, developed by the Harvard-MIT Observatory of Economic Complexity.
3) The King of Treemaps — Smart Money’s Map of the Market — offers a classic set of measures: size represents market cap; color represents change in market cap.
3 Bad Examples:
1) The category labels use space -- almost as if you added slices to a pie chart for labeling. This approach distorts the values by arbitrarily using space, making it harder for the viewer to visually compare sizes.
2) Labels clutter up this tree map, can't read, not helpful!
3) These text boxes look clunky, obscure some of the data, and don’t always fit into the allotted space.