Create and analyze graphs with NetworkX in Python.
npx skills add https://github.com/ManfronEnrico/thesis-manifold --skill networkx-manfronenrico
Please help me install this Agent Skill. Skill: networkx Source: https://github.com/ManfronEnrico/thesis-manifold/tree/main/.claude/skills/networkx Command: npx skills add https://github.com/ManfronEnrico/thesis-manifold --skill networkx-manfronenrico
NetworkX provides a Python toolkit for creating, manipulating, and analyzing complex networks and graphs, enabling researchers and engineers to model relationships, compute graph metrics, and visualize structures without reinventing core algorithms.
Create a small graph with a few nodes and edges, then run a shortest-path or centrality analysis.
High-intent search queries and answers about installing and using this skill.
Compute centrality and shortest paths by creating a graph object and calling built-in algorithms. The toolkit provides deterministic methods to derive connectivity insights from social, biological, or transportation networks.
Yes, you can import and export graph data from GraphML, GML, JSON, CSV, and adjacency formats. This interoperable data exchange supports reading and writing complex network structures for analysis.
Network visualization and analysis require a Python environment with NetworkX installed. The toolkit integrates with Python to create publication-ready figures and compute graph metrics for various network types.
Model relationships by creating and manipulating flexible network structures like Graph, DiGraph, or MultiGraph. This approach enables researchers to analyze connectivity without reinventing core graph algorithms.
Yes, the toolkit supports community detection and clustering algorithms. These graph algorithms help derive structural insights from connectivity patterns in citation, knowledge, and social networks.
Use Python for graph metrics when you need deterministic algorithms and comprehensive documentation for common graph tasks. It suits researchers modeling complex networks across social, biological, and transportation domains.
mkurmanCreate, analyze, and visualize complex networks and graphs in Python.
SALTYf1SHConvert experimental metrics into publication-ready figures and tables.
nferrer-devCreate, manipulate, and analyze complex network graphs with standard algorithms.
K-Dense-AIAnalyze and manipulate graphs in Python using NetworkX's Graph, DiGraph and MultiGraph types and algorithms.
