drawing_mode attribute of node in Treemaps defines how branches headers and data item labels are displayed. It defines whether branches will expand their content on all chart when they are clicked, or not.Īlthough treemaps give a great opportunity to show a lot of data in a limited space, you can't always place all texts on the chart. node has enable_drilldown attribute which can be "true" or "false". It can be "asc", "desc" - default, and "none" - you will get "as they go" in XML file order. node has sort attribute, which defines how sub-nodes of each branch are sorted. There are several special things about treemap charts.įirst of all there is a special node in style that defines how tree branches are shown, you can define, , and for them - so user can easily distinguish them among other elements. You can either visualize linear and hierarchical data using An圜hart treemaps, if, for example, you have the following data set listing countries population: The illustration below shows structure of Treemap charts in An圜hart: Treemaps in An圜hart are build using a special plot_type named"TreeMap". As a result, they can legibly display thousands of items on the screen simultaneously. A second advantage of treemaps is that, by construction, they make efficient use of space. When the color and size dimensions are correlated in some way with the tree structure, one can often easily see patterns that would be difficult to spot in other ways. Often the leaf nodes are colored to show a separate dimension of the data. A leaf node's rectangle has an area proportional to a specified dimension on the data. Each branch of the tree is given a rectangle, which is then tiled with smaller rectangles representing sub-branches. When pasted into PowerPoint, Chart Animation does not work with Treemap and Sunburst type of charts.Treemaps display hierarchical (tree-structured) data as a set of nested rectangles. However, you can always use Pivot table reference and draw a regular chart from it (not PivotChart).Īnother type of new chart called Sunburst is also designed for hierarchical data. These new charts require data in a very specific way.
This is because, Pivot Table can layout data in so many different ways. However, Treemap (and many of the new charts) do NOT work directly with Pivot table. Remember that Pivot Tables often have hierarchical data and are good candidates for Treemaps. Remember to try Treemaps with hierarchical data next time onwards. What we have in the chart above is Overlapping labels. Right click on any item and choose Format Data Series. In the chart above, category names and sub category names have the same appearance visually. are the categories and Emp / Outsourced are the sub-categories. Much more easier to interpret – within as well as across categories.ĭisplaying the Category label more prominentlyįinance, Marketing, etc. If the data was like this, a pie chart cannot be drawn at all. That is how you will interpret things better. Notice that the relative importance of these two areas is much easier to assess when it is a rectangle rather than a pie. Try to interpret the relative importance of various data points in the treemap.įor easy comparison use the black and purple areas in both charts. It is available in all editions on all devices (including Mobile Phones). Now compare this pie chart with the other chart. In many cases, the percentages or data labels are not shown on top of the chart – leaving the job of interpretation entirely to us. Multiple such pieces confuse our vision and therefore the relative size interpreted by us need not necessarily be the actual size. In case of Pie charts, we are supposed to compare pieces which are an arc – a piece of the pie. Treemaps are a good tool for displaying things like best-selling products, location population, regional sales, and similar parent-child structured data. How accurate that picture is – that is the real question. As mentioned, treemaps are intended to work with hierarchical data, and this data has one-to-many relationships.
If you look at two pieces of the pie, you form a mental picture of their relative sizes. The problem with pie charts is that of interpretation accuracy. I have intentionally removed all the Data Labels and Legend. Here is the data which is used to draw both the above charts. Pie charts show the proportion of various data points in a series. Displaying the Category label more prominently.