ds-cheatsheets
A collection of links to data science cheatsheets (PDFs) for Python, R, SQL, math and machine learning.
- Stars
- 16.4k
- Forks
- 4k
- Licence
- MIT
- Language
- —
- Last update
- 2.3 years ago
- Type
- Curated list
No commits in over a year — check for forks or alternatives before adopting.
What it is
This is a curated list of downloadable one-page reference sheets covering data science topics such as Python, R, pandas, SQL, statistics, machine learning, deep learning and data visualization. Each entry links to a PDF hosted in the repository or in linked rstudio and business-science cheatsheet collections. It is meant as a quick reference people can print or keep open while working.
- Open the pandas or numpy basics PDF while writing code
- Print the SQL cheat sheet for quick query syntax reminders
- Browse the machine learning sections to pick a model family to read about
- Use the R tidyverse or ggplot2 sheets while learning R
Great for
- Beginners who want quick reference sheets for Python or R
- Students reviewing math, statistics or machine learning basics
- Data analysts looking up pandas, dplyr or SQL syntax
- Teachers who want printable reference material to share
Not ideal for
- People who need full tutorials or step-by-step courses, since these are short reference sheets
- Anyone who needs up-to-date library documentation, because the last push was 2024-07-18 and some sheets may be dated
How to get it
- 1
Read it online
Clone the repository to get a local copy of the PDFs
git clone https://github.com/FavioVazquez/ds-cheatsheets - 2
Run it
- Open the repository page at github.com/FavioVazquez/ds-cheatsheets
- Pick a topic from the table of contents, such as Python or SQL
- Click a PDF link to view or download the cheat sheet
- 3
Get the most out of it
- Browse the Python folder for Datacamp-style basics sheets for pandas, numpy and matplotlib
- Use the R section for tidyverse, data.table and ggplot2 references
- Check the Machine Learning section for supervised and unsupervised learning sheets
Downloads
Strengths
- Large collection of reference sheets across many topics
- Sheets are free to download and MIT-licensed as a list
- Organized by language and subject in the README table of contents
Trade-offs
- Content is only links to PDFs, with no explanations or code to run
- Some sheets may be outdated relative to current library versions
- README is truncated, so the full list of entries could not be verified
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| ds-cheatsheets (this) | 16.4k | Curated list | beginner | 2.3 years ago | Beginners who want quick reference sheets for Python or R |
| PayloadsAllTheThings | 82.3k | Curated list | beginner | 7 days ago | Penetration testers who want a quick reference of payload variations for a known vulnerability class |
| homemade-machine-learning | 24.8k | Learning resource | beginner | 12 months ago | Students learning the math behind machine learning algorithms |
| awesome-cheatsheets | 12.6k | Curated list | beginner | 2 months ago | Chinese-speaking developers who want quick command or syntax reminders |
| ML-For-Beginners | 91.9k | Learning resource | beginner | 6 days ago | Beginners who want a structured, self-paced introduction to machine learning |
| 33-js-concepts | 66.5k | Learning resource | beginner | 16 days ago | Developers who know basic JavaScript and want to fill gaps in core concepts |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.