To spot patterns, outliers, most-important contributors, and exceptions. To show attributes using size and color coding. To show the pattern of the distribution of the measure across each level of categories in the hierarchy. To show the proportions between each part and the whole. When a bar chart can't effectively handle the large number of values. To display large amounts of hierarchical data. You could compare the number of items sold across the other clothing categories by comparing the size and shading of each leaf node larger and darker rectangles mean higher value. Lots of other rectangles for all the other clothing sold. Slightly smaller rectangles for Natura and Fama. The largest rectangle for VanArsdel in the top-left corner. So, the Urban branch of your Treemap has: In the Urban branch above, lots of VanArsdel clothing was sold. These leaves would be sized and shaded based on the number sold. Power BI would split your category rectangles into leaves, for the clothing manufacturers within that category. The rectangles are arranged in size from top left (largest) to bottom right (smallest).įor example, if you're analyzing your sales, you might have top-level branches for the clothing categories: Urban, Rural, Youth, and Mix. Power BI bases the size of the space inside each rectangle on the measured value. Each level of the hierarchy is represented by a colored rectangle (branch) containing smaller rectangles (leaves). Treemaps display hierarchical data as a set of nested rectangles. APPLIES TO: ✔️ Power BI Desktop ✔️ Power BI service