# shervinea/mit-15-003-data-science-tools

Study guides for MIT's 15.003 Data Science Tools

Repository: https://github.com/shervinea/mit-15-003-data-science-tools
Canonical: https://ross.abutalabs.com/products/mit-15-003-data-science-tools
Homepage: https://www.mit.edu/~amidi/teaching/data-science-tools/
License: MIT
License Family: permissive
Topics: study-guide, data-science, sql, r, git, bash, manipulation, visualization, retrieval
Last push: 2020-08-23T16:27:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2215, "days_push": 2201, "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 1945, forks 378 (observed 2026-08-28T04:05:57.709476+00:00)

## What it is
A collection of illustrated study guides and cheatsheets for MIT's 15.003 Data Science Tools course, covering SQL, R, Python, Git, and Bash. It includes R-to-Python conversion guides and a combined 'super study guide' compilation, available as PDFs and web pages in multiple languages.

## Use cases
- learn SQL joins and window functions with a concise study guide
- find pandas equivalents for dplyr and tidyr operations
- review matplotlib and seaborn plotting concepts quickly
- brush up on Git and Bash commands before an interview
- study data manipulation and visualization fundamentals for a data science course

## When to choose
- you want compact, illustrated reference material for SQL, R, Python, Git, or Bash
- you are transitioning between R and Python and need side-by-side conversion tables
- you are a student of MIT 15.003 or a similar introductory data science course

## When to avoid
- you need in-depth tutorials or hands-on exercises rather than condensed cheatsheets
- you need up-to-date coverage of the latest library APIs, as the guides were last released in 2020
- you are looking for runnable code or a software tool rather than reference documents

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, documentation, developer-tools
- domain: data-science, tutorials, education, developer-tools
- platform: cross-platform
- tags: study-guide, cheatsheets, sql, r, python, git, bash, data-visualization, data-manipulation, mit-course

## Member repositories
- shervinea/mit-15-003-data-science-tools (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:57.709476+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 2026-08-30T03:07:58.882052+00:00, confidence not recorded.
  - readme: https://github.com/shervinea/mit-15-003-data-science-tools (fetched 2026-08-28T04:05:57.709476+00:00, sha 3ebb650d79a8)
  - homepage: https://www.mit.edu/~amidi/teaching/data-science-tools/ (fetched 2026-08-29T10:47:18.387985+00:00, sha b8d2d83b1431)
- Data as of 2026-08-30T08:39:29.467469+00:00.