# iamseancheney/python_for_data_analysis_2nd_chinese_version

《利用Python进行数据分析·第2版》

Repository: https://github.com/iamseancheney/python_for_data_analysis_2nd_chinese_version
Canonical: https://ross.abutalabs.com/products/python_for_data_analysis_2nd_chinese_version
License Family: other
Topics: numpy, pandas, matplotlib
Last push: 2026-08-26T01:32:23+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2995, "days_push": 8, "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 8980, forks 2739 (observed 2026-08-28T04:10:26.604292+00:00)

## What it is
A Chinese translation of the second edition of 'Python for Data Analysis' (Wes McKinney), hosted as a readable online resource covering NumPy, pandas, and matplotlib. It is a study/translation project rather than software.

## Use cases
- learn pandas in Chinese
- study numpy and matplotlib from a book
- read Python for Data Analysis 2nd edition in Chinese
- learn data analysis with Python
- find a Chinese version of Wes McKinney's book

## When to choose
- you prefer Chinese-language learning material for pandas/NumPy
- you want the 2nd edition content of Python for Data Analysis

## When to avoid
- you need the latest 3rd edition content
- you need executable code or a maintained library
- you only read English

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, nlp
- domain: data-science, tutorials, education
- platform: python, cross-platform
- tags: chinese-translation, numpy, pandas, matplotlib, book-translation, python-for-data-analysis

## Member repositories
- iamseancheney/python_for_data_analysis_2nd_chinese_version (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:26.604292+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 2026-08-29T17:24:24.623925+00:00, confidence not recorded.
  - readme: https://github.com/iamseancheney/python_for_data_analysis_2nd_chinese_version (fetched 2026-08-28T04:10:26.604292+00:00, sha cc842d67eedb)
- Data as of 2026-08-30T08:39:29.467469+00:00.