# tdpetrou/Learn-Pandas

Tutorials on how to use pandas effectively to do data analysis

Repository: https://github.com/tdpetrou/Learn-Pandas
Canonical: https://ross.abutalabs.com/products/learn-pandas
Language: Jupyter Notebook
License: BSD-3-Clause
License Family: permissive
Last push: 2022-11-30T17:49:26+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3206, "days_push": 1372, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1114, forks 320 (observed 2026-08-28T04:03:38.158720+00:00)

## What it is
A collection of Jupyter Notebook tutorials teaching how to use the pandas library effectively for data analysis in Python. It accompanies the author's book 'Master Data Analysis with Python'.

## Use cases
- learn pandas for data analysis
- understand dataframe manipulation in python
- find pandas tutorial notebooks
- get started with data analysis in python
- improve pandas skills for filtering and aggregating data

## When to choose
- you are learning pandas from scratch or want structured tutorial notebooks
- you prefer example-driven learning in Jupyter Notebooks

## When to avoid
- you need a maintained software library or tool rather than tutorials
- you need up-to-date coverage of the latest pandas APIs

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science
- domain: data-science, tutorials, education
- platform: python
- tags: pandas, data-analysis, jupyter-notebook, tutorials

## Member repositories
- tdpetrou/Learn-Pandas (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:38.158720+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 2026-08-30T06:42:32.541458+00:00, confidence not recorded.
  - readme: https://github.com/tdpetrou/Learn-Pandas (fetched 2026-08-28T04:03:38.158720+00:00, sha 661afb5c7991)
- Data as of 2026-08-30T08:39:29.467469+00:00.