networkx

Create, manipulate, and analyze complex networks in Python.

1|1|Updated Mar 13, 2026

Search Tags:#python #algorithms #visualization #data structures #network analysis #graph

Ready to run

npx skills add https://github.com/youyinnn/skills-collection --skill networkx-youyinnn

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/youyinnn/skills-collection/tree/main/plugins/model-development-and-experiments/skills/networkx
Command: npx skills add https://github.com/youyinnn/skills-collection --skill networkx-youyinnn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python, simplifying the process of understanding relationships and structures within data.

Core Features & Use Cases

Graph Creation: Build network structures from various data sources.
Algorithm Execution: Apply algorithms for centrality, shortest paths, community detection, etc.
Data I/O: Read from and write to numerous graph file formats.
Visualization: Generate static and interactive network visualizations.
Use Case: Analyze a social network to identify key influencers by computing their centrality measures, or model a transportation system to find the shortest routes between locations.

Quick Start

Use the networkx skill to draw a spring layout of the karate club graph and save it as 'karate_club.png'.

Frequently Asked Questions about networkx

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

FAQPage Schema

How do I analyze a social network to identify key influencers using Python?▼

You can analyze a social network by creating a graph structure from your data and executing centrality algorithms to compute influence metrics, identifying key nodes based on their positions within the network.

What is the best way to find shortest paths in a transportation system model?▼

Finding shortest paths in a transportation system model involves representing locations as nodes and routes as edges, then applying shortest path algorithms to traverse the graph and calculate the most efficient routes.

How do I create and visualize complex network graphs with pandas and numpy?▼

You can create complex network graphs by building structures from data sources and generate visualizations by integrating with matplotlib, pandas, and numpy for comprehensive data handling and static or interactive display.

Can I read and write numerous graph file formats for network analysis?▼

Yes, you can read from and write to numerous graph file formats. This data I/O capability allows you to easily import existing network structures and export your analyzed graphs for use in other applications.

How does community detection work for complex networks in Python?▼

Community detection for complex networks works by applying specialized algorithms to graph structures to identify densely connected groups of nodes, revealing the underlying functional dynamics and modular organization of the network.