The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain code, equations, visualizations and text. The functionality is partly overlapping with Quarto (see the tutorial), in that they both use markdown and code chunks to generate reports that integrate results of computations with the code that generated them. Jupyter Notebook comes from the Python community while Quarto was developed by Posit (who also created R Markdown and RStudio), but you could use most common programming languages in either alternative. In practice though, it’s quite common that R developers use Jupyter but probably not very common that Python developers use RStudio. Some reasons to use Jupyter include:

Python is lacking a really good IDE for doing exploratory scientific data analysis, like RStudio or Matlab. Some people use Jupyter simply as an alternative for that.
The Jupyter Project community is large and dynamic, and there are lots of tools for sharing, displaying or interacting with notebooks.
An early ambition with Jupyter notebooks (and its predecessor IPython notebooks) was to be analogous to the lab notebook used in a wet lab. It would allow the data scientist to document his or her day-to-day work and interweave results, ideas, and hypotheses with the code. From a reproducibility perspective, this is one of the main advantages.
Jupyter notebooks can be used, just like Quarto, to provide a tighter connection between your data and your results by integrating results of computations with the code that generated them. They can also do this in an interactive way that makes them very appealing for sharing with others.

As always, the best way is to try it out yourself and decide what to use it for!

This tutorial depends on files from the course GitHub repo. Take a look at the setup for instructions on how to set it up if you haven’t done so already. Then open up a terminal and go to workshop-reproducible-research/tutorials/jupyter and activate your jupyter-env Conda environment.

A note on nomenclature

Jupyter: a project to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Lives at jupyter.org.

Jupyter Notebook: A web application that you use for creating and managing notebooks. One of the outputs of the Jupyter project.

Jupyter lab: A more powerful and feature-rich interface that also includes a terminal, debugger, tabs etc.

Jupyter notebook: The actual .ipynb file that constitutes your notebook.