# hangsz/pandas-tutorial

适合初级到中级晋升者，有了体系之后就看熟练度了。

Repository: https://github.com/hangsz/pandas-tutorial
Canonical: https://ross.abutalabs.com/products/pandas-tutorial
Language: Jupyter Notebook
License Family: other
Topics: python, pandas
Last push: 2024-03-30T02:58:39+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": 3294, "days_push": 886, "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 1890, forks 412 (observed 2026-08-28T04:05:49.491389+00:00)

## What it is
A Chinese-language pandas tutorial in Jupyter Notebooks covering Series/DataFrame operations, merge, groupby, time handling, and more, from beginner to intermediate. It emphasizes a coherent knowledge system with concise, hands-on examples.

## Use cases
- learn pandas from scratch
- build a systematic understanding of pandas
- practice dataframe operations with short examples
- level up from beginner to intermediate pandas
- understand merge and groupby in pandas
- find a structured alternative to pandas docs

## When to choose
- you prefer Chinese-language tutorials
- you want a systematic, example-driven pandas curriculum
- you are a beginner or intermediate data science practitioner

## When to avoid
- you need English-language material
- you need an exhaustive API reference
- you need a maintained library rather than a tutorial

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, developer-tools
- domain: data-science, tutorials, education
- platform: python
- tags: pandas, jupyter-notebook, chinese-language, beginner-friendly

## Member repositories
- hangsz/pandas-tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:49.491389+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 2026-08-30T03:13:01.787998+00:00, confidence not recorded.
  - readme: https://github.com/hangsz/pandas-tutorial (fetched 2026-08-28T04:05:49.491389+00:00, sha 08b3ef505918)
  - registry_pypi: https://pypi.org/pypi/pandas-tutorial/json (fetched 2026-08-29T10:52:12.269043+00:00, sha 68ea88a27372)
- Data as of 2026-08-30T08:39:29.467469+00:00.