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networkx

Create, analyze, and visualize complex networks with Python algorithms.

1|Updated Mar 12, 2026
Search Tags:#python#algorithms#visualization#data structures#network analysis#graph
One-click install
npx skills add https://github.com/yf8578/clawomics --skill networkx-yf8578
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/yf8578/clawomics/tree/main/skills/networkx
Command: npx skills add https://github.com/yf8578/clawomics --skill networkx-yf8578

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, transforming raw relational data into actionable insights.

Core Features & Use Cases

  • Graph Creation & Manipulation: Build and modify various graph types (undirected, directed, multi-graphs) with rich attributes.
  • Advanced Algorithms: Perform complex analyses like shortest path finding, centrality measures, community detection, and flow calculations.
  • Data Integration & Visualization: Read/write from multiple formats and generate clear, publication-quality network visualizations.
  • Use Case: Analyze a social network to identify key influencers, detect communities, and visualize the network structure to understand relationships and information flow.

Quick Start

Use the networkx skill to create a complete graph with 5 nodes and draw it using a spring layout.

Frequently Asked Questions about networkx

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

FAQPage Schema
How do I analyze complex networks and graph structures in Python?▼

To analyze complex networks in Python, you can use this Skill to create, manipulate, and study graph structures. It enables graph generation, algorithm execution for shortest paths, centrality measures, and community detection.

What is the best way to visualize relational data and detect communities in a graph?▼

Visualizing relational data and detecting communities requires executing network analysis algorithms. This Skill provides graph generation, community detection algorithms, and integrates with plotting libraries to generate publication-quality network visualizations.

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

Yes, you can build and modify various graph types including undirected, directed, and multi-graphs. The Skill supports adding rich attributes to nodes and edges for comprehensive network manipulation.

Does this Skill support reading and writing multiple graph data formats?▼

Yes, this Skill supports reading and writing graphs from multiple input and output formats. This allows you to integrate existing relational data structures into your network analysis workflow seamlessly.

How do I identify key influencers in a social network?▼

To identify key influencers in a social network, apply centrality measures and shortest path algorithms. This Skill executes these network analysis functions to help you understand relationships and information flow.

What are the limitations of using Python for large-scale network analysis?▼

While this Skill provides advanced algorithms for network analysis, its performance depends on the Python environment. Complex network manipulation and visualization of extremely large graphs may require integration with specialized plotting libraries.

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