rougier/numpy-100 resource
100 numpy exercises (with solutions) observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 99
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4481
- days_rel: n/a
- days_push: 7
- n_releases_24m: 0
Adoption not part of the score
14390 stars · 6894 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A collection of 100 NumPy exercises with solutions, sourced from the NumPy mailing list, Stack Overflow, and documentation. It is distributed as Jupyter notebooks and markdown, runnable interactively via Binder.
Use cases
- learn numpy through practice problems
- find numpy exercises for teaching a class
- quick reference for numpy operations
- practice python array manipulation
- prepare for data science interviews with numpy questions
When to choose
- you want hands-on numpy practice with solutions available
- you need ready-made exercises for teaching numpy
- you want a quick lookup of common numpy idioms
When to avoid
- you need a numpy tutorial with explanations rather than exercises
- you are looking for a production library or tool
Facets
learning-resource · maturity stable
developer-tools data-science data-science education tutorials python cross-platform numpy exercises jupyter-notebook binder learning
1 source
- readme: https://github.com/rougier/numpy-100 · fetched 2026-08-28 · 279379a2f012
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| rougier/numpy-100 | main | 67 |
For agents
markdown · JSON · MCP: product_card(name="rougier/numpy-100")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem