Jupyter Notebooks have been popular among Python users for years, but with JupyterLab it's now possible to write notebooks in other languages. As part of the Summer Tech Update, the SSCC has set up JupyterLab on Linstat such that Stata, R, Julia, and SAS users can use Jupyter Notebooks as well as Python users.
JupyterLab is an easy-to-use programming environment. The user interface runs in a browser on your computer so it's not affected by network lag, but the code is run on Linstat so you have plenty of computing power. The only Linux you need to know is how to specify a directory. We think many SSCC researchers will be interested in JupyterLab purely for writing code, especially Julia and Python users where the alternatives are lacking.
Jupyter Notebooks can contain text (optionally formatted using Markdown), code, and the results of running that code, all in a single convenient file. They're great for collaboration, informal communication of results, and especially teaching. Tools like Quarto can easily convert Notebooks into web pages, PDF files, LaTeX, and more. Collections of Notebooks can be converted into web "books." For example, Converting Stata Loops to Parallel Loops Using Slurm (The Easy Way) and Data Wrangling in Python were both written as Jupyter Notebooks using JupyterLab.
In this workshop we'll spend the bulk of the time learning how to use JupyterLab, including Markdown. We'll then discuss some of the ways Notebooks can be used in research and teaching.>
Room: 3218 Sewell Social Sciences Building
Time: 2:00 - 3:00