Notebook Driven Development

Learn to create reproducible research with data science notebooks, hvPlot visualizations, and automated multi-notebook pipelines using PyDoIt and Papermill.

This course offers researchers and graduate students a practical, hands-on introduction to working with data science notebooks for scientific analysis and reproducible research. Data science notebooks provide an integrated environment where code, figures, and narrative explanations come together to support exploration, documentation, and communication of results.

Participants will learn to use tools such as hvPlot for creating informative visualizations, and explore techniques for generating presentation-ready outputs directly from their analyses. The course also introduces advanced methods using PyDoIt and Papermill to build modular, multi-notebook pipelines that can run analyses across varying parameters and datasets. By the end of the workshop, participants will be equipped to create reusable, well-documented code libraries and automate batch processing workflows. No prior programming experience is required—this course is open to researchers from all disciplines.

Credits

pixi install --manifest-path pixi.toml
pixi shell

conda env create -f environment.yml
conda activate ndd