skills.rest
felixboehm
felixboehmCOMMUNITY
Explore all skills by this author →
GitHub

networkx

Create, analyze, and visualize complex networks with Python.

Updated Mar 10, 2026
Search Tags:#python#algorithms#visualization#data structures#network analysis#graph
One-click install
npx skills add https://github.com/felixboehm/biochem-allergy --skill networkx-felixboehm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/felixboehm/biochem-allergy/tree/main/.claude/skills/networkx
Command: npx skills add https://github.com/felixboehm/biochem-allergy --skill networkx-felixboehm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs, enabling users to understand intricate relationships and structures within data.

Core Features & Use Cases

  • Graph Creation & Manipulation: Build and modify various graph types (undirected, directed, multi-graphs).
  • Algorithm Execution: Run standard graph algorithms like shortest path, centrality, community detection, and more.
  • Data I/O & Visualization: Read/write graphs from/to multiple formats and generate visual representations.
  • Use Case: Analyze a social network to identify influential users (centrality), map out community structures, and visualize the network's topology.

Quick Start

Use the networkx skill to draw a spring layout of the karate club graph with labels.

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 influential users in Python?▼

To analyze a social network for influential users, this Skill provides Python algorithms to calculate centrality measures and map community structures within complex graph data.

What Python data structures do I need for modeling complex networks?▼

Modeling complex networks requires precise definition of nodes, edges, and their attributes to accurately represent structures like biological or transportation systems.

Can I create and manipulate directed graphs and multi-graphs using Python?▼

Yes, you can create and manipulate various graph types including directed graphs and multi-graphs to study the dynamics and functions of complex networks.

How do I generate visual representations of graph structures?▼

Generating visual representations of graph structures is supported through built-in visualization tools that render network topology and layouts like a spring layout.

Does this network analysis toolkit support reading and writing multiple graph formats?▼

Yes, the network analysis toolkit supports reading and writing graphs from and to multiple formats for flexible data I/O and integration.

What is the best way to find the shortest path in a complex graph?▼

The best way to find shortest paths is using the built-in standard graph algorithms provided for analyzing complex networks and routing structures.

Related Skills

Explore More Software Engineering Skills→
silversteinsilverstein
21

networkx

Create and analyze graph structures with NetworkX in Python.

Community
Advanced
semantica-agisemantica-agi
3.0k

visualize

Visualize Semantica knowledge graph topology, centrality, communities, paths, and temporal evolution.

Official
Intermediate
Ritabrata-ChakrabortyRitabrata-Chakraborty

networkx

Create, analyze, and visualize complex networks and graphs in Python.

Community
Advanced
Hawksight-AIHawksight-AI
2.9k

visualize

Analyze graph topology and generate visual summaries of knowledge graphs.

Official
Advanced