https://github.com/fralfaro/ds-cheat-sheets
Data Science Cheat Sheets
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.4%) to scientific vocabulary
Keywords
Repository
Data Science Cheat Sheets
Basic Info
- Host: GitHub
- Owner: fralfaro
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://ds-cheat-sheets.streamlit.app/
- Size: 21.7 MB
Statistics
- Stars: 24
- Watchers: 1
- Forks: 5
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Cheat Sheets for Data Science Learning

Welcome to the Ultimate Data Science Cheat Sheet Repository, thoughtfully designed for Python and R enthusiasts.
The official link to the Streamlit application is https://ds-cheat-sheets.streamlit.app/, where you can explore the cheat sheets in three different formats:
- 🚀 Streamlit: Fully interactive and user-friendly.
- 📄 PDF: Easily downloadable and perfect for quick reference.
- 💻 Google Colab: Pre-configured and ready for hands-on learning.
Sections
Additionally, we’ve provided a neatly organized table below, listing all the available files for quick access to their different formats.
📗 Python
| Topic | PDF | Streamlit | Google Colab |
|--------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| python | |
|
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| numpy |
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|
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| pandas |
|
|
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| matplotlib |
|
|
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| scikit-learn |
|
|
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| polars |
|
|
|
📘 R
| Topic | PDF | Streamlit | Google Colab |
|---------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| dplyr | |
|
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| ggplot2 |
|
|
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| forcats |
|
|
|
Note: The PDF format cheat sheets included here are authored by other contributors and have been used as sources of inspiration for the content presented.
More Information
What is a Cheat Sheet ?
A cheat sheet is a concise and informative reference guide that provides quick and easy access to essential information or instructions about a specific topic.
It's designed to help individuals quickly understand key concepts, commands, formulas, or procedures without having to search through lengthy documentation or resources. Cheat sheets are often used as handy reference tools for tasks that require familiarity with specific details or steps, such as programming languages, software applications, or academic subjects. They serve as a valuable aid for both beginners and experienced practitioners by condensing important information into a single, easily digestible format.
What is Streamlit ?
Streamlit is an open-source Python library that simplifies and accelerates the process of creating interactive web applications for data science and machine learning projects. It allows developers, data scientists, and researchers to transform data scripts into shareable web applications quickly and with minimal effort.

What is Jupyter Notebook ?

Jupyter Notebook is an open-source web application that provides an interactive and flexible environment for creating, sharing, and executing documents that contain live code, equations, visualizations, and explanatory text. It's widely used by researchers, data scientists, educators, and professionals to develop and present code-based projects, analyses, and reports.

What is Google Colab ?

Google Colab, short for Google Colaboratory, is a cloud-based, interactive development environment provided by Google that enables users to write, execute, and share Python code in a collaborative and convenient manner. It's particularly popular among researchers, data scientists, and educators for its ease of use and the fact that it doesn't require any setup or installation.

📖 References
Owner
- Name: Francisco
- Login: fralfaro
- Kind: user
- Website: fralfaro.github.io/portfolio/
- Repositories: 8
- Profile: https://github.com/fralfaro
GitHub Events
Total
- Watch event: 9
- Push event: 7
- Fork event: 3
Last Year
- Watch event: 9
- Push event: 7
- Fork event: 3
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
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Dependencies
- actions/checkout v2 composite
- actions/setup-python v2 composite
- peaceiris/actions-gh-pages v3 composite
- mkdocs-jupyter *
- mkdocs-material *
- neoteroi-mkdocs *
- python ^3.10