#Treemap chart data software

Getter/setter for the compare method used to sort sibling blocks. Getter/setter for whether to exclude the root node from the representation.

Getter/setter for the minimum area of a block (in square px) required for it to be rendered in the DOM. Determines the CSS class(es) to apply to each block node. Getter/setter for a node object classname accessor. Getter/setter for a node object color accessor, used to color the blocks. Getter/setter for the amount of padding between adjacent blocks, in px. Getter/setter for a node object size accessor, used to compute the areas of the blocks. Getter/setter for a node object label accessor, used to display labels on the blocks and their tooltips. Supports either a string indicating the object's property name, or a function(node) which should return an array of nodes. Getter/setter for a data node's children accessor, used to establish the hierarchical relationship between nodes. Getter/setter for the chart height in px. The rectangles are colored by the type of company, and the rectangles are grouped by companyР’В size.Getter/setter for chart data (see below for syntax details). We also have a variable for theР’В sizesР’В ofР’В theР’В companies.Р’В This example shows more categories of companies than the previous examples.Р’В The rectangles are sized by average sales in US dollars. NowР’В we have a variableР’В for different types of companies with six levels. Figure 3 shows similarР’В financialР’В dataР’В as is presented in Figure 2. TreemapsР’В areР’В moreР’В useful forР’В largerР’В sets ofР’В variables withР’В a large number ofР’В levels. Example 2: Categories and hierarchy for larger sets of variables with many levels However, by usingР’В the category variable, we see that the original conclusion that medium-sized companies have the highest profits/employee is not true. The original conclusion that large companies have the highest average sales is still true. Tools that provide РІР‚Сљhover helpРІР‚Сњ or allow interactive drill-down are helpful here. ThisР’В situationР’В is common with larger sets of dataР’В that result inР’В many small rectangles. TheР’В treemap cannot label theР’В smallest rectangleР’В for the small pharmaceutical companies.

We also see that medium-sized computer companies have a negative profit/employee. The rectangles are sized by the average sales (in US dollars) for the categories of companies and colored by the profits per employee.Р”Р‡rom the treemap in Figure 2, we see that the profit/employee is highest for small pharmaceutical companies.Р’В From the rectangle sizes, we see that large companies in both categories have the highest sales. The very simpleР’В treemapР’В in Figure 1 shows theР’В structure of sales forР’В small, medium and large companies. Some tools allow drill-down to show more detail, which is useful when aР’В treemapР’В has small rectanglesР’В and the labels cannot be seen easily. Most tools have an option to color the rectangles and can add labels to them.

#Treemap chart data software

Software toolsР’В use an algorithm to construct the size ofР’В rectangles proportionalР’В to the number of observations that fall within each rectangle. TreemapsР’В are almost always computer-generated. Treemaps originated as a way to show the structure andР’В size of filesР’В onР’В a computer hard drive.Р’В TreemapsР’В are now used for many situations, including those without a hierarchy.Р’В TreemapsР’В can show a large amount of data in a small amount of space.

AР’В treemapР’В is an arrangement of rectangles that shows the hierarchicalР’В structureР’В of your data.