# jakevdp/PythonDataScienceHandbook

Python Data Science Handbook: full text in Jupyter Notebooks

Repository: https://github.com/jakevdp/PythonDataScienceHandbook
Canonical: https://ross.abutalabs.com/products/pythondatasciencehandbook
Homepage: http://jakevdp.github.io/PythonDataScienceHandbook
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: scikit-learn, numpy, python, jupyter-notebook, matplotlib, pandas
Last push: 2024-06-26T19:17:33+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3675, "days_push": 798, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 49705, forks 19092 (observed 2026-08-28T04:12:11.660370+00:00)

## What it is
The full text of Jake VanderPlas's Python Data Science Handbook, freely available as Jupyter notebooks covering IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It can be read online, run locally, or executed via Google Colab or Binder.

## Use cases
- learn pandas for data manipulation
- learn numpy array computing
- learn matplotlib data visualization
- learn scikit-learn machine learning basics
- free python data science book with runnable notebooks
- introduction to ipython and jupyter workflows

## When to choose
- you want a free, well-regarded introduction to the core Python data science stack
- you prefer learning through executable Jupyter notebooks
- you need a reference for NumPy, Pandas, Matplotlib, or Scikit-Learn fundamentals

## When to avoid
- you need up-to-date coverage of the latest library APIs (the book was written for Python 3.5-era versions)
- you want advanced or specialized machine learning topics beyond the fundamentals
- you need a formal course with exercises and grading

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, data-visualization, machine-learning, nlp
- domain: data-science, tutorials, education, data-visualization, machine-learning
- platform: python, cross-platform
- tags: jupyter-notebooks, numpy, pandas, matplotlib, scikit-learn, ipython, free-book, oreilly, web

## Member repositories
- jakevdp/PythonDataScienceHandbook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:11.660370+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:20:11.362335+00:00, confidence not recorded.
  - readme: https://github.com/jakevdp/PythonDataScienceHandbook (fetched 2026-08-28T04:12:11.660370+00:00, sha 3d3a3f13d8c8)
  - homepage: http://jakevdp.github.io/PythonDataScienceHandbook (fetched 2026-08-28T18:13:02.752442+00:00, sha 40932823d352)
- Data as of 2026-08-30T08:39:29.467469+00:00.