1k stars · MIT · release-0.7.3 (2026-05-31)
Labelled data maps with proper label placement — a diagnostic for cluster naming and a shareable marketing image.
▶Repo detailsthe review · specs · pros & cons · install
What it is
A plotting library for labelled data maps. It places cluster labels so they do not collide, renders the point cloud with proper density handling instead of a scatter of dots, and exports either a publication-quality static figure or a self-contained interactive HTML page with search and hover.
Why it matters
Two uses, and one of them is marketing. As a tool: it is by far the fastest way to see whether 09's names and your clustering are any good — one figure over one real conversation teaches you more than reading a list of label strings ever will. As a marketing asset: a properly labelled map of every question asked inside a 500-message thread is the picture that explains Grasppy in a single frame, which is exactly what your landing page, your Satori social images and your thumbnails currently lack. Images like that get shared on their own merits, which is a rarer property than it sounds. Same institute as 09, so the two are designed to sit next to each other.
- MIT, pure Python, and no front-end work — a figure or a standalone HTML page straight from a dataframe
- Label placement is the genuinely hard part of a map like this, and it is the part that is already solved
- The interactive export is self-contained, so it drops into an Astro page with no build step at all
- It draws a point cloud, not a hierarchy. This is a design and diagnostic tool, not the drill-in canvas — that is still React Flow plus elkjs
- It wants 2-D coordinates, so UMAP has to sit in front of it: another dependency, and another non-deterministic step you must seed
- Static export goes through matplotlib, whose font handling with Cyrillic is where the fiddly hour will go
Same institute as 09, so the two are designed to sit next to each other.
source venv/bin/activate pip install datamapplot