Rectangular Drill-down Voronoi Tree Map
A weighted Voronoi treemap is a specialized data visualization technique that combines the concepts of Voronoi diagrams and treemaps. It partitions a given space into regions based on a set of weighted data points. Each region represents a data item or category, and its size is proportional to the weight associated with that item. By using Voronoi tessellation, which ensures that each data point is associated with the nearest region, weighted Voronoi treemaps offer an effective way to visually represent hierarchical and weighted data structures. These treemaps are particularly useful in areas such as financial analysis, resource allocation, and data visualization, where both hierarchy and weight are important factors to consider.
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Build this chart with AI
The prompt below can be used to build this chart with AI. For best coding results, use the most advanced AI models, like Claude Opus 4.6 and GPT-5.3-Codex. For more info and tips, check out amCharts AI docs.
Create a rectangular Voronoi treemap displaying world population data organized by continents and countries. The hierarchy should have a root (World), six continents (Africa, Asia, Europe, North America, South America, Oceania), and individual countries with population values. Countries with small populations should be grouped into an 'Others' category per continent. Use rectangular Voronoi polygon partitioning where area is proportional to population. Style continent-level polygons with thick black borders, and country-level polygons with thin borders and no fill. Dynamically show full country names for larger regions or short country codes for smaller areas. Enable drill-down navigation by clicking a country to zoom to its parent continent. Animate with a smooth staggered animation. Use amCharts 5 library.
Demo source