Interactive Notebooks
Project Jupyter
jupyter.org
a next-generation Python notebook
marimo.ioInteractive Notebooks are a type of computational document that combines code execution, narrative text, equations, visualizations, and other media in a single, interactive environment. They're particularly popular in data science, machine learning, and scientific computing for their ability to blend explanatory text with executable code. Here's how Python, Jupyter, R Studio + R Markdown, and Bookdown fit into this concept:
- Python: Python itself is a high-level programming language. However, it can be used in the context of interactive notebooks through various tools.
- Jupyter Notebooks: This is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It supports multiple languages including Python, R, Julia, and others, but is most commonly associated with Python (hence "Jupyter" sometimes being referred to as 'Jupyter Notebook' in the context of Python). Notebooks consist of cells - either code cells or markdown cells. Code cells contain executable code (Python, R, etc.), while markdown cells can hold text formatted using Markdown syntax. When a cell is executed, its output (text, plots, data, etc.) appears below it.
- Posit + R Markdown: R is another popular language for statistical computing and graphics. RStudio is an integrated development environment (IDE) for R. R Markdown is a format for creating dynamic documents with R code, embedded output (like plots), and narrative text. It allows you to mix R code and its output with Markdown syntax for formatting the document. When you "knit" an .Rmd file in RStudio, it runs your R code, captures the results, and weaves them into a cohesive report that can be exported as HTML, PDF, Word documents, and more.
- Bookdown: Bookdown is an R package that extends the functionality of R Markdown by providing a collection of formats and tools for writing books and long-form articles. It allows you to write in Markdown, embed R code (and output), LaTeX equations, images, and more, and then compile your work into various book formats like HTML, PDF, or EPUB. Bookdown is particularly useful for creating comprehensive, narrative-driven documents that include both text and computational elements, such as data analyses, tutorials, or scientific reports.
All these tools support the concept of interactive notebooks by enabling users to write, execute, and present code alongside descriptive text and visuals in a single, interactive document. This makes them ideal for teaching, research, data analysis, and storytelling in data science, machine learning, and other computational fields.