# datawhalechina/hands-on-data-analysis

动手学数据分析以项目为主线，知识点孕育其中，通过边学、边做、边引导来得到更好的学习效果

Repository: https://github.com/datawhalechina/hands-on-data-analysis
Canonical: https://ross.abutalabs.com/products/hands-on-data-analysis
Language: Jupyter Notebook
License Family: other
Last push: 2024-05-29T04:52:55+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": 2241, "days_push": 826, "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 1524, forks 384 (observed 2026-08-28T04:04:58.245959+00:00)

## What it is
An open-source Chinese-language hands-on course from Datawhale that teaches data analysis through project-based Jupyter notebooks covering pandas/numpy basics, data cleaning, visualization, and sklearn modeling. It pairs course exercises with reference answers and is designed for group learning.

## Use cases
- learn pandas and numpy for data analysis
- beginner course on the data analysis workflow
- practice data cleaning and feature engineering
- learn exploratory data analysis with real datasets
- get started with sklearn modeling and model evaluation
- follow a structured data analysis tutorial with exercises and answers

## When to choose
- you are a beginner wanting a guided, project-driven introduction to data analysis in Python
- you prefer learning by doing with Jupyter notebooks and reference solutions
- you want a free course covering the full pipeline from loading data to modeling and evaluation

## When to avoid
- you need advanced or production-grade data engineering or MLOps material
- you require a maintained software library or tool rather than course content
- you need English-language instruction or a formally licensed resource

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, etl, machine-learning, data-visualization
- domain: data-science, tutorials, education
- platform: python, cross-platform
- tags: pandas, numpy, sklearn, jupyter-notebooks, data-cleaning, exploratory-data-analysis, chinese, datawhale, hands-on-course

## Member repositories
- datawhalechina/hands-on-data-analysis (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:58.245959+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 2026-08-30T04:31:42.298521+00:00, confidence not recorded.
  - readme: https://github.com/datawhalechina/hands-on-data-analysis (fetched 2026-08-28T04:04:58.245959+00:00, sha bff965a66ec4)
- Data as of 2026-08-30T08:39:29.467469+00:00.