Analyze Graph Data with Python
Apply graph algorithms at scale using the Python GDS client and Aura Graph Analytics
In this 4-hour workshop, you will learn
Welcome to the Go to glossary for graph data science (opens in a new tab)Analysing data through the structure of its connections. Also the name of the Neo4j library that implements it. Python Client & Go to glossary for Aura Graph Analytics (opens in a new tab)The Aura service that runs graph algorithms in a separate session, with no plugin to install. workshop.
In this hands-on workshop, you will move from the Neo4j Browser to the Python GDS client, applying Full definition for centrality (opens in a new tab)How important a node is within a graph. Each centrality algorithm defines importance differently., Full definition for community detection (opens in a new tab)A family of algorithms that group nodes by how they connect. Each algorithm defines a community differently., and Full definition for embedding (opens in a new tab)Information represented as a numerical vector, positioned so that similar information sits close together. algorithms to a citation network. You'll then learn to run Full definition for pathfinding (opens in a new tab)A family of algorithms that find routes through a graph. What counts as the best route differs by algorithm. algorithms at scale using Aura Graph Analytics.
Before taking this workshop, you should have:
- Completed the Graph Data Science in Practice workshop, or equivalent experience with GDS concepts
- Basic understanding of GDS Full definition for projection (opens in a new tab)An in-memory copy of part of your database that graph algorithms run against. You choose which nodes and relationships it holds. and the Project → Run → Write workflow
- Familiarity with Python
GDS Python Client
Aura Graph Analytics
PageRank
Betweenness Centrality
FastRP
What you need to take part.
A GraphAcademy account
The workshop is delivered here on GraphAcademy, so you need to be signed in to work through the lessons and keep your progress. Creating an account is free.
A GitHub account, or Git on your own machine
You write code against the workshop-gds-python-aga repository. The quickest route is a GitHub Codespace, an online editor that clones the code and installs everything for you — that needs a GitHub account.
If you would rather work locally, clone the repository with Git and run it in your own editor instead. No GitHub account is needed for that.