A graphical toolkit for visualization Protovis

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Gallery Enjoy these sample visualizations built with Protovis. For any example, use your browser to view the source or the backing dataset. Protovis is no longer under active development.



D3.js, with improved support for animation and interaction. D3 builds on many of the concepts in Protovis; for more details, please read the The final release of Protovis was v3.3.1 (4.7 MB) . The Protovis team is now developing a new visualization library,, with improved support for animation and interaction. D3 builds on many of the concepts in Protovis; for more details, please read the introduction and browse the examples Enjoy these sample visualizations built with Protovis. For any example, use your browser to view the source or the backing dataset.

Hierarchies Many datasets can be organized into natural hierarchies. Consider: spatial entities, such as counties, states, and countries; command structures for businesses and governments; software packages and phylogenetic trees. Even for data lacking apparent hierarchy, statistical methods such as k-means clustering may be applied to organize data empirically. Special visualization techniques exist to leverage hierarchical structure, allowing multiscale inferences of both individual elements and global trends. Dendrograms Sunbursts Icicles Indented Trees Circle Packing Node-Link Trees Treemaps



Networks Graph visualizations often seek to reveal relationship patterns between entities and groups in the underlying dataset. For example, given a social network, who are the central players, and what cliques or bridges exist? Can multivariate data (such as gender or affiliation) explain those patterns? Arc Diagrams Force-Directed Layouts Matrix Diagrams

