J j Allaire Jupyter Notebooks + Quarto for customizable and reproducible documents, websites and
To share our results and communicate effectively in data science, we need to weave together narrative text and code to produce elegantly formatted, interactive output. Not only does it need to look great, but it needs to be reproducible, accessible, easily editable, diffable, version controlled and output in a variety of formats, such as PDF, HTML and MS Word for convenience and often compliance. Jupyter has already made so much of this possible. By combining Jupyter with the open-source publishing platform, Quarto, built on Pandoc, you can easily create the output format and the styling that you need for any situation. With Quarto, you can author documents as plain text markdown or Jupyter notebooks with scientific markdown, including equations (LaTeX support!), citations, cross references, figure panels, callouts, advanced layouts, and more. You can also engage readers by adding interactive data exploration to your documents using Jupyter Widgets, htmlwidgets for R, Observable JS, and Shiny.
In this talk, we’ll discuss authoring these dynamic, computational documents with Quarto and Python that bring code, output, and prose together, leveraging integrations with both Jupyter and the Quarto VS Code extension. Whether you’re new to Jupyter or have thousands of notebooks already, we’ll walk you through using a single source document to target multiple formats - transforming a simple document into a presentation, a scientific manuscript, a website, a blog, and a book in a variety of formats including HTML, PDF and MS Word. We’ll also show how you can change themes and styling, and publish these artifacts directly from the command line to the web, so they’re immediately available online
Quarto
Shiny
JupyterCon2023
DataScienceInnovation
JupyterCommunity
PythonProgramming
OpenSourceTools
DataVisualization
InteractiveComputing
DataAnalysis
NotebookWorkflow
JupyterLove
DataDrivenInsights
MachineLearning
AIinAction
ResearchTools
CodingInJupyter
