networkx

Create and analyze complex networks with Python graph algorithms.

19|2|Updated Jan 31, 2026

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

Ready to run

npx skills add https://github.com/tondevrel/scientific-agent-skills --skill networkx-tondevrel

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/tondevrel/scientific-agent-skills/tree/main/skills/networkx
Command: npx skills add https://github.com/tondevrel/scientific-agent-skills --skill networkx-tondevrel

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, matplotlib, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you understand the structure, dynamics, and functions of complex networks by providing tools for creation, manipulation, and analysis.

Core Features & Use Cases

Network Creation: Build various graph types (directed, undirected, multigraphs).
Algorithm Library: Utilize standard graph algorithms for pathfinding, centrality, community detection, and more.
Use Case: Analyze a social network to identify influential users (centrality measures) or optimize delivery routes in a transportation network (shortest path algorithms).

Quick Start

Use the networkx skill to find the shortest path between nodes 'A' and 'D' in graph G, considering edge weights.

Frequently Asked Questions about networkx

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

FAQPage Schema

How do I find the shortest path in a weighted graph using Python?▼

To find the shortest path in a weighted graph, this Skill uses Python network analysis algorithms to compute optimal routes between nodes. It handles edge weights for accurate infrastructure optimization and delivery route planning.

What is network analysis and how does it identify influential users in social networks?▼

Network analysis identifies influential users in social networks by applying centrality measures to graph structures. This Skill calculates node importance using standard graph algorithms to reveal social network dynamics and functions.

Can I use Python to create and manipulate directed and undirected graphs?▼

Yes, you can create and manipulate directed, undirected, and multigraphs using Python. This Skill provides tools for building complex networks and performing structural studies using Python data structures and graph theory algorithms.

Does this network analysis Skill require matplotlib and scipy for visualization?▼

Yes, this Skill requires matplotlib and scipy for visualization and computation. These dependencies support rendering complex network structures and performing mathematical operations required by standard graph algorithms.

What's the best way to optimize delivery routes in a transportation network?▼

The best way to optimize delivery routes is applying shortest path algorithms to a transportation network. This Skill uses standard graph algorithms to calculate optimal paths between nodes, considering edge weights for infrastructure optimization.

When do I need community detection algorithms for complex networks?▼

You need community detection algorithms when analyzing complex networks to identify clusters or groups of densely connected nodes. This Skill includes a comprehensive library of standard graph algorithms for network analysis.