Data science Notebooks are a powerful tool that allows you to combine code, figures, and written explanations all in one place! Join us in this three-day, hands-on workshop, where we will extract the best out of data science notebooks by learning how to embed explanations, create beautiful plots using hvPlot, generate presentations from our analyses, and even advanced techniques that leverage PyDoIt and Papermill to build multi-notebook pipelines, run the analyses across varying parameters, batch process across mutiple datasets, and even develop fully-documented libraries of reusable code! This course is open to all researchers, with or without experience in a programming language.

Learning and participation

Topics

  • Exploratory data analysis with Pandas and hvPlot on Jupyter Lab.
  • Access contents of a notebook from another notebook and creating parameterized analysis notebooks with papermill.
  • We use PyDoIt to create and manage a workflow of fully-documented notebooks.

Intended participants

  • Researchers and students from all universities are welcome.
  • Participants of all educational backgrounds are welcome.

Certification

Students who attend at least 75% of the course will receive a participation certificate by email at the end of the course.