# WillKoehrsen/Data-Analysis

Data Science Using Python

Repository: https://github.com/WillKoehrsen/Data-Analysis
Canonical: https://ross.abutalabs.com/products/data-analysis
Homepage: https://medium.com/@williamkoehrsen/
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2023-07-08T14:08:19+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": 3458, "days_push": 1152, "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 5566, forks 3608 (observed 2026-08-28T04:09:22.416451+00:00)

## What it is
A collection of Jupyter notebooks and code for numerous data science projects in Python (with a little R) by Will Koehrsen. It serves as a learning resource accompanying his Towards Data Science articles.

## Use cases
- learn data analysis with python notebooks
- find example data science projects to study
- learn exploratory data analysis techniques
- study machine learning project walkthroughs
- get hands-on python data science examples

## When to choose
- you want worked examples of data science projects in Python
- you are learning data analysis and want notebook-style tutorials
- you want code accompanying Will Koehrsen's Medium articles

## When to avoid
- you need a production-ready library or tool
- you need maintained, tested software with an API
- you need a structured curriculum rather than a notebook collection

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, data-visualization, machine-learning
- domain: data-science, education, tutorials
- platform: python
- tags: jupyter-notebooks, tutorials, example-projects, exploratory-data-analysis

## Member repositories
- WillKoehrsen/Data-Analysis (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:22.416451+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 2026-08-29T17:55:36.915882+00:00, confidence not recorded.
  - readme: https://github.com/WillKoehrsen/Data-Analysis (fetched 2026-08-28T04:09:22.416451+00:00, sha 3e3e45eb6578)
- Data as of 2026-08-30T08:39:29.467469+00:00.