How to visualize a social network in Python with a graph database
· 2 min read
Originally published on Towards Data Science
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Social networks are a natural fit for graph data: people are nodes, relationships are edges, and the questions you actually care about — who's central, which communities form, how information spreads — are questions about structure.
This walkthrough builds an end-to-end app for exploring one:
- A graph database to store the network and answer traversal queries directly, instead of forcing relationships into rows and joins.
- Flask as a thin Python backend exposing the graph to the frontend over a small API.
- Docker to wire the pieces together so the whole thing runs with a single command.
- D3.js to render the network in the browser as an interactive, force-directed graph you can actually pan, zoom, and inspect.
The result is a live, explorable picture of a social graph — the kind of visualization that makes structure obvious in a way a table never will.