# FavioVazquez/ds-cheatsheets

List of Data Science Cheatsheets to rule the world

Repository: https://github.com/FavioVazquez/ds-cheatsheets
Canonical: https://ross.abutalabs.com/products/ds-cheatsheets
License: MIT
License Family: permissive
Topics: datascience, python, r, spark, programming, jupyter, cheatsheet
Last push: 2024-07-18T03:39:29+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": 2813, "days_push": 776, "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 16330, forks 4043 (observed 2026-08-28T04:11:15.097733+00:00)

## What it is
A curated collection of data science cheatsheets in PDF format covering Python, R, Spark, machine learning, and business science workflows. It aggregates reference sheets from sources like Datacamp, Dataquest, and RStudio into one repository.

## Use cases
- find a pandas cheatsheet pdf
- quick reference for numpy syntax
- learn dplyr data transformation shortcuts
- python regex cheat sheet
- spark and big data reference sheets
- study material for data science interviews

## When to choose
- you want quick printable reference sheets for data science tools
- you are learning Python, R, or Spark and need concise syntax reminders
- you want a curated index of existing cheatsheets in one place

## When to avoid
- you need executable code or a software library
- you need in-depth tutorials rather than condensed references
- you need up-to-date documentation for the latest library versions

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, data-science
- domain: data-science, tutorials, awesome-lists, education
- platform: cross-platform
- tags: cheatsheets, python, r, spark, jupyter, reference

## Member repositories
- FavioVazquez/ds-cheatsheets (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:15.097733+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 2026-08-29T17:05:08.855022+00:00, confidence not recorded.
  - readme: https://github.com/FavioVazquez/ds-cheatsheets (fetched 2026-08-28T04:11:15.097733+00:00, sha c5d97a3da28a)
- Data as of 2026-08-30T08:39:29.467469+00:00.