Tree Map Charts
Gallery Index

Chart Types
Pie Charts (1) Pie Charts (2) Bar Charts (1) Bar Charts (2) Line Charts (1) Line Charts (2) Area Charts Trending Charts Box Charts Scatter Charts 3D Scatter Charts Contour Charts Surface Charts Discrete Heat Maps Tree Map Charts Bubble Charts Vector Charts Gantt Charts Finance Charts Combo Charts Polar Charts (1) Polar Charts (2) Pyramids/Funnels Meters/Gauges (1) Meters/Gauges (2) Meters/Gauges (3) Meters/Gauges (4)

User Interactions
Track Cursors Clickable Charts Zooming/Scrolling Real-Time Charts
  • A tree map chart is like a pie chart. They both partition a shape into smaller shapes proportional to the data values. A pie chart partition a circle into slices, while a tree map chart partition a rectangle into smaller rectangles.

  • As a tree map chart partition rectangles into smaller rectangles, it is possible to recrusively partition the smaller rectangles into even smaller rectangles. Thus a tree map can have multiple levels of branching, and that is why it is called a tree map.

  • In the previous example, the tree map is colored based on the first level partition. ChartDirector can also color the rectangles based on the second level partition or use other custom coloring.

  • Squarify is one of the most common methods to partition the rectangle. It aims to make the rectangles as close to squares as possible. This method will but the largest rectangle at one corner (configurable, usually the top-left corner), and the smallest retangle at the opposite corner.
  • The Strip method lays out the rectangles from left to right and top to bottom in the order of the original data, like flowing text (other directions are also supported). This allows the user to easily look up a particular rectangle.
  • The number of items in each row is such that the rectangles are as close to squares as possible. As the data are not sorted, a row can contain both wide and thin rectangles, and the rectangles will not be as close to squares as the Squarify method.
  • Like the Strip method, the Binary Spilt by Size method does not change the data order.
  • This method splits the data series into two shorter series so that their total data values are as equal as possible. It then splits the rectangle into two smaller rectangles proportional to the total data values, and assign the shorter series to the smaller rectangles. The method is recrusively applied to the shorter series until the each series contains one item.
  • In each step, the rectangle can be splitted left/right or top/bottom. The direction is chosen such that the smaller rectangles are as close to squares as possible.
  • The Binary Split by Count method is the same as the Binary Split by Size method, except the data series is splitted in the middle so that the number of elements in the two series are as equal as possible.