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networkx

Create and analyze complex graphs in Python with NetworkX.

Updated Apr 2, 2026
Search Tags:#visualization#graphs#io#networkx#centrality#shortest-path#networks
One-click install
npx skills add https://github.com/viniruggeri/applied-dynamical-systems --skill networkx-viniruggeri
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/viniruggeri/applied-dynamical-systems/tree/main/.agents/skills/networkx
Command: npx skills add https://github.com/viniruggeri/applied-dynamical-systems --skill networkx-viniruggeri

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

NetworkX provides a flexible toolkit for creating, manipulating, and analyzing the structure of complex networks and graphs in Python, enabling researchers and developers to model relationships, compute metrics, and visualize connectivity without implementing algorithms from scratch.

Core Features & Use Cases

  • Graph construction and manipulation with multiple graph types (Graph, DiGraph, MultiGraph, MultiDiGraph) and attributes.
  • Algorithms for shortest paths, centrality, clustering, community detection, and connectivity.
  • IO and visualization: read/write formats (GraphML, GML, JSON, CSV), and render layouts.
  • Use cases: social, biological, transportation networks; knowledge graphs; network science experiments.

Quick Start

Install NetworkX, create a graph, add nodes and edges, then run a quick analysis and visualize it.

Frequently Asked Questions about networkx

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze social or biological networks in Python?▼

To analyze social or biological networks in Python, you can build graphs and compute metrics like centrality, clustering, and community detection without implementing algorithms from scratch.

What is the best way to compute shortest paths in a complex graph?▼

The best way to compute shortest paths in a complex graph is using a dedicated network analysis library that provides built-in algorithms for connectivity and routing.

How do I import and export GraphML or GML files for network visualization?▼

You can import and export GraphML or GML files for network visualization by using IO functions that read and write these formats, alongside JSON and CSV.

Can I build directed and undirected graphs with custom attributes in Python?▼

Yes, you can build directed and undirected graphs with custom attributes in Python by using multiple graph types like Graph, DiGraph, and MultiGraph.

Do I need Python installed to use this Skill for network analysis?▼

Yes, you need Python installed to use this Skill for network analysis, as it requires a Python environment with the NetworkX library available to run computations.

Can I render network layouts using matplotlib or Plotly?▼

Yes, you can render network layouts using matplotlib or Plotly to visualize complex graphs and connectivity structures after running your analysis.

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