NetworkX Graph Analysis
Analyzes complex networks and relational datasets using NetworkX graph data structures, centrality algorithms, community detection, and visualizations.
NetworkX Graph Analysis equips Claude Code with comprehensive capabilities to create, manipulate, and examine complex relational data across biological networks, social systems, and transportation graphs. It supports undirected, directed, and multi-edge networks alongside essential algorithms for shortest paths, centrality metrics (PageRank, betweenness, degree), and modularity-based community detection. With built-in integration for Pandas, SciPy sparse matrices, standard graph I/O formats (GraphML, GML, edge lists), and Matplotlib visual layouts, this skill streamlines end-to-end topological analysis and network exploration directly in your Python workflows.