PyGraphistry AI

Doc routing (local + canonical)

• First route with ../pygraphistry/references/pygraphistry-readthedocs-toc.md.
• Use ../pygraphistry/references/pygraphistry-readthedocs-top-level.tsv for section-level shortcuts.
• Only scan ../pygraphistry/references/pygraphistry-readthedocs-sitemap.xml when a needed page is missing.
• Use one batched discovery read before deep-page reads; avoid cat * and serial micro-reads.
• In user-facing answers, prefer canonical https://pygraphistry.readthedocs.io/en/latest/... links.

Typical workflow

1. Build graph from nodes/edges.
2. Run feature/embedding method (umap, embed, optional dbscan).
3. Inspect derived columns/features and visualize.
4. Iterate on feature columns and sampling strategy.

Baseline examples

# Similarity embedding / projection
g2 = graphistry.nodes(df, 'id').umap(X=['f1', 'f2', 'f3'])