# apachecn/python_data_analysis_and_mining_action

《python数据分析与挖掘实战》的代码笔记

Repository: https://github.com/apachecn/python_data_analysis_and_mining_action
Canonical: https://ross.abutalabs.com/products/python_data_analysis_and_mining_action
Language: Python
License Family: other
Topics: readingnotes, python3, data-science, data-analysis
Last push: 2020-08-02T10:30:01+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": 3230, "days_push": 2222, "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 1807, forks 702 (observed 2026-08-28T04:05:39.153992+00:00)

## What it is
Annotated Python source code and notes accompanying the Chinese book 'Python Data Analysis and Mining in Action', organized by chapter with code and data files. Published by ApacheCN as an open learning resource with online, PDF, EPUB, and MOBI editions.

## Use cases
- learn data analysis with python from a book
- study data mining techniques with worked examples
- find companion code for the python data analysis and mining book
- practice pandas and sklearn on real datasets
- reference annotated examples for data cleaning and modeling
- learn machine learning in chinese with code notes

## When to choose
- you are reading the book and want its code with explanations
- you want chapter-by-chapter runnable examples with datasets
- you prefer learning data mining through annotated source code

## When to avoid
- you need a production data analysis library or framework
- you want actively maintained tooling rather than book notes
- you need English-language materials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, nlp
- domain: data-science, tutorials, machine-learning
- platform: python
- tags: reading-notes, book-companion, data-mining, chinese, example-code, data-engineering

## Member repositories
- apachecn/python_data_analysis_and_mining_action (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.153992+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 2026-08-30T03:21:26.138988+00:00, confidence not recorded.
  - readme: https://github.com/apachecn/python_data_analysis_and_mining_action (fetched 2026-08-28T04:05:39.153992+00:00, sha cac4d040e6eb)
- Data as of 2026-08-30T08:39:29.467469+00:00.