Tools for Data Science: A Comprehensive Guide

Essential Tools from VSCode to Docker, Git, Quarto, Jupyter, and Mutagen

Explore the wide range of tools available for data science workflows. This section covers topics from Visual Studio Code, Docker, Git, Quarto, Jupyter and Mutagen.

Tools
Author
Affiliation

Alboukadel Kassambara

Datanovia

Published

March 9, 2025

Modified

March 11, 2025

Keywords

data science tools, VSCode, Docker, Git, Quarto, Jupyter, Mutagen

Tools for Data Science

Data science workflows rely on a variety of tools to ensure efficiency, reproducibility, and scalability. In this section, you’ll find resources on essential tools ranging from code editors and container platforms to version control and interactive notebooks. Our topics include:

  • Visual Studio Code
    Learn about setting up VSCode for data science, programming in R and Python, and using specialized extensions.

  • Docker
    Discover Docker basics for data science, how to run Docker with Python and R, and creating custom Docker images for your projects.

  • Git
    Explore Git fundamentals, best practices for data scientists, and managing projects on GitHub and GitLab.

  • Quarto
    Get started with Quarto for reproducible reporting and learn how to create dynamic documents with Python and R.

  • Jupyter
    Find tutorials on using JupyterHub, hosting servers, and leveraging advanced notebook features for interactive analysis.

  • Mutagen
    Access our comprehensive tutorials on Mutagen, a high-performance tool for real-time file synchronization between your local environment and containers.

Note:
Currently, only the Mutagen tutorials have been documented in detail. Check back soon for more content on the other tools!

Explore Mutagen Tutorials

Enhance your containerized development workflows by mastering file synchronization with Mutagen. Our Mutagen series covers:

What’s Next?

We are continually working to expand our Tools category. In the near future, expect to see detailed tutorials on:

  • Visual Studio Code for Data Science
  • Docker and Custom Container Environments
  • Git Best Practices for Data Scientists
  • Reproducible Reporting with Quarto
  • Advanced Jupyter Notebook Techniques

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Citation

BibTeX citation:
@online{kassambara2025,
  author = {Kassambara, Alboukadel},
  title = {Tools for {Data} {Science:} {A} {Comprehensive} {Guide}},
  date = {2025-03-09},
  url = {https://www.datanovia.com/learn/tools/index.html},
  langid = {en}
}
For attribution, please cite this work as:
Kassambara, Alboukadel. 2025. “Tools for Data Science: A Comprehensive Guide.” March 9, 2025. https://www.datanovia.com/learn/tools/index.html.