Create, analyze, and visualize graphs with Python and NetworkX.
npx skills add https://github.com/jackspace/ClaudeSkillz --skill networkx-jackspace
Please help me install this Agent Skill. Skill: networkx Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/scientific-pkg-networkx Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill networkx-jackspace
NetworkX provides tools to create, analyze, and visualize graphs and networks; ideal for social networks, transportation, biology, and more.
Install NetworkX and run a quick example to create a graph and compute a shortest path.
High-intent search queries and answers about installing and using this skill.
NetworkX is a Python toolkit that creates, analyzes, and visualizes graphs across domains like social networks, transportation, and biology. It supports four graph types (Graph, DiGraph, MultiGraph, MultiDiGraph) and provides algorithms for shortest paths, centrality, clustering, and community detection.
NetworkX implements shortest path, centrality measures, clustering coefficients, community detection, flow algorithms, minimum spanning trees, and PageRank. These algorithms work across directed, undirected, and multigraph structures for network analysis.
Yes, NetworkX supports diverse I/O formats including edge lists, GraphML, JSON, CSV, and adjacency matrices. You can read and write graphs to these formats, enabling integration with other tools and data pipelines.
NetworkX integrates with matplotlib for static graph visualization and supports interactive libraries for dynamic visualization. You can render network layouts, node positions, and edge relationships directly from your graph objects.
Yes, NetworkX includes graph generators to create synthetic networks with specific properties. These generators support common network models for testing algorithms and simulating real-world network structures.
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