Originally designed to visualize files on a hard drive, Treemaps have been applied to a wide variety of domains ranging from financial analysis to sports reporting ( Ordered Treemap Layouts, Ben Shneiderman, Martin Wattenberg, ). At the same time, Treemaps are not designed to convey numerical quantities the intent is to show relative ranking and relative differences in data-set values. It shows the relative weight of data points at more than one level (represented as a rectangle) letting you continuously drill down deeper into the data set that is represented by smaller rectangles for more efficient analysis. Unlike the arguably most popular part-to-whole visualization, the Pie Chart, a Treemap Chart is designed for drill-down scenarios. Categories are shown in proportion to other categories based on their value percentage to the total value being analyzed. While a Treemap is sometimes categorized as a “distribution” visualization, I see it mostly referred to as a “part-to-whole” visualization, showing categories (parts) of a data set that add up to a total (whole) value.