skills.rest
Clay-HHK
Clay-HHKCOMMUNITY
Explore all skills by this author →
GitHub

networkx

Create, manipulate, and analyze graph data in Python.

2|Updated Apr 12, 2026
Search Tags:#python#visualization#data-analysis#graphs#networkx#graph-analysis
One-click install
npx skills add https://github.com/Clay-HHK/claude-config --skill networkx-clay-hhk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: networkx
Source: https://github.com/Clay-HHK/claude-config/tree/main/skills/networkx
Command: npx skills add https://github.com/Clay-HHK/claude-config --skill networkx-clay-hhk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

NetworkX provides a comprehensive framework for building, analyzing, and visualizing graphs and networks in Python, turning complex relational data into actionable insights without heavy boilerplate.

Core Features & Use Cases

  • Graph creation and manipulation across Graph, DiGraph, MultiGraph, and MultiDiGraph.
  • Graph algorithms for shortest paths, centrality, clustering, connectivity, and community detection.
  • IO and visualization support for practical workflows in research, data science, and software engineering.

Quick Start

Load a simple undirected graph and compute basic metrics.

Frequently Asked Questions about networkx

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

FAQPage Schema
How do I analyze network graphs in Python without writing complex boilerplate code?▼

NetworkX provides a comprehensive Python framework for graph analysis, turning complex relational data into actionable insights without heavy boilerplate. It supports rapid creation and manipulation of graph structures.

What graph algorithms are available for finding shortest paths and detecting communities?▼

Graph algorithms for shortest paths, centrality, clustering, connectivity, and community detection are built into NetworkX. These algorithms enable detailed structural analysis of network data directly in Python.

Can I model both directed and undirected network graphs using this approach?▼

You can model network graphs across multiple types including standard Graph, DiGraph, MultiGraph, and MultiDiGraph. This flexibility accommodates both directed and undirected relational data structures.

Does NetworkX require specific Python data libraries to load and process graph data?▼

NetworkX requires Python and common data libraries to load, process, and output network metrics. It is designed for workflows in research, data science, and software engineering.

How do I visualize network graphs and handle graph I/O in my data analysis workflow?▼

NetworkX includes IO and visualization support for practical workflows in research and data science. These tools allow you to import graph data, compute metrics, and output visual network representations.

Related Skills

Explore More Data & Analytics Skills→
googlegoogle
17.1k

bigquery-basics

Automate BigQuery dataset, table, and job management with SQL queries.

Official
Intermediate
shushuznshushuzn
4

networkx

Build and analyze complex networks with NetworkX graph metrics.

Community
Advanced
ptreezhptreezh
24

performing-network-computation

Build social network graphs and compute indicators, centralities, and community structure.

Community
Intermediate
curiositechcuriositech
181

hr-network-analyst

Analyze professional networks to identify key influencers using graph theory and centrality metrics.

Official
Advanced