# lijin-THU/notes-python

中文 Python 笔记

Repository: https://github.com/lijin-THU/notes-python
Canonical: https://ross.abutalabs.com/products/notes-python
Language: Jupyter Notebook
License Family: other
Topics: python, scipy, theano, matplotlib, anaconda, numpy
Last push: 2020-10-01T15:06:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3982, "days_push": 2162, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7151, forks 2844 (observed 2026-08-28T04:09:56.259747+00:00)

## What it is
A collection of Chinese-language Python learning notes presented as Jupyter Notebooks, covering Python basics, IPython, NumPy, SciPy, Pandas, and Matplotlib. It is a tutorial-style educational repository rather than a software package.

## Use cases
- learn python basics in chinese
- study numpy and scipy with jupyter notebooks
- beginner python tutorial with examples
- learn scientific computing in python
- reference notes for pandas and matplotlib
- self-study python for data analysis

## When to choose
- you are a Chinese-speaking beginner learning Python fundamentals
- you want notebook-based lessons on the scientific Python stack
- you prefer free self-study material with runnable examples

## When to avoid
- you need up-to-date material for modern Python 3 practices (notes target Python 2.7)
- you need a maintained library or tool rather than learning content
- you need officially licensed material for commercial adaptation

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools, data-science, documentation
- domain: education, data-science, tutorials, programming-languages
- platform: python, cross-platform
- tags: jupyter-notebook, chinese-language, numpy, scipy, pandas, matplotlib, scientific-computing, python-tutorial

## Member repositories
- lijin-THU/notes-python (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:56.259747+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 2026-08-29T17:40:00.158914+00:00, confidence not recorded.
  - readme: https://github.com/lijin-THU/notes-python (fetched 2026-08-28T04:09:56.259747+00:00, sha 6d63dedefc7f)
- Data as of 2026-08-30T08:39:29.467469+00:00.