Jupyter Notebooks are a powerful tool for researchers to organize and document their research process. In this workshop, we will cover best practices for using Jupyter Notebooks in research and provide hands-on demonstrations to help attendees better understand the benefits and limitations of this tool.

Learning Outcomes

  • Understanding the basics of Jupyter Notebooks and how they can be used in research
  • Best practices for organizing and documenting research processes within Jupyter Notebooks
  • Hands-on demonstrations of using Jupyter Notebooks to organize, document, and visualize research results
  • Understanding the limitations of Jupyter Notebooks and how to overcome them
  • Tips and tricks for using Jupyter Notebooks effectively in research

Who Should Attend

This workshop is designed for academics and industry professionals who are looking to better organize their research process and take advantage of the benefits of Jupyter Notebooks. No prior experience with Jupyter Notebooks is required.

Jupyter Notebooks in the Research Process

Jupyter notebooks are a powerful tool for researchers to organize, document, and share their work. In this workshop, we will cover best practices for effective use of Jupyter notebooks as they pertain to interests and goals in the research “pipeline”.

Benefits of Using Jupyter Notebooks

  • Reproducibility: Jupyter notebooks allow you to document every step of your research process, from data import to analysis and visualization. This makes it easy to share your work and recreate your results.

  • Collaboration: Jupyter notebooks allow multiple people to work on the same project, making it easier to collaborate with others.

  • Ease of use: Jupyter notebooks provide an intuitive interface that makes it easy to code, experiment, and visualize results.

Best Practices

  1. Organization: Keep your notebooks organized by using clear and descriptive names for each notebook, adding relevant tags and descriptions, and using a consistent file structure.

  2. Code modularity: Break down your code into smaller, reusable pieces by creating functions and modules. This makes it easier to maintain your code and reuse parts of it for future projects.

  3. Documentation: Add comments and markdown cells to document your code and explain what you are doing. This makes it easier for others to understand your work and for you to look back at your code later on.

  4. Version control: Use version control (such as Git) to keep track of changes to your notebooks and collaborate with others.

  5. Packaging: Put re-usable code into a centralized place and use your notebooks to import these functionalities

  6. Testing: Use unit tests to validate your code and make sure that it is working as expected.

  7. Visualization: Use visualizations to help explain and communicate your results. Make sure that your visualizations are clear and informative.

  8. Sharing: Share your notebooks with others by using platforms such as GitHub or Google Colab.

By following these best practices, you can make the most of Jupyter notebooks in your research process and ensure that your work is organized, understandable, and reproducible.

Workshop Structure

  1. Introduction to Jupyter Notebooks

    • Overview of Jupyter Notebooks
    • How to install and launch Jupyter Notebook
    • Jupyter Notebook interface and basic functionality

  2. Best Practices for Jupyter Notebook Usage in Research

    • Organizing notebooks into a structure that makes sense for your project
    • Writing clear and concise markdown cells
    • Storing and version controlling notebooks with Git
    • Using Jupyter Notebooks to record and share findings with collaborators

  3. JupyterHub: Collaborative Jupyter Notebooks

    • What is JupyterHub
    • How to install and launch JupyterHub
    • Best practices for hosting JupyterHub for a team
    • Managing users, authentication and access control
    • Setting up a multi-user environment for reproducible research

  4. Hands-On Activities

    • Setting up a Jupyter Notebook for a research project
    • Working with Markdown cells and LaTeX equations
    • Using Jupyter Notebook to perform data analysis and visualizations
    • Sharing Jupyter Notebooks with collaborators
    • Setting up and using JupyterHub for a team of researchers

  5. Conclusion

    • Summary of key concepts learned
    • Discussion of future directions for Jupyter Notebook usage in research
    • Q&A session to address any remaining questions

See the workshop structure page for more information about general workshop format.