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Summary
Jupyter (jupyter.org) is a framework for managing code “notebooks” of cells, mixed code, text, images, and graphics. Users access to math, science, engineering, communication, and visualization tools on an open-source, web-based platform.
Jupyter Notebook allows you to program in a web browser. Users can write live code, equations, visualizations, and narrative text, then share their Notebooks with others through email, GitHub, and the Jupyter Notebook Viewer in a single place. It is an open-source web application built for collaboration.
Features
- Language of choice: Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala.
- Share notebooks: Notebooks can be shared with others using email, Dropbox, GitHub, and the Jupyter Notebook Viewer.
- Interactive output: Your code can produce rich, interactive output: HTML, images, videos, LaTeX, and custom MIME types.
- Big data integration: Leverage big data tools, such as Apache Spark, from Python, R, and Scala. Explore that same data with pandas, scikit-learn, ggplot2, TensorFlow.
Who can use it?
Example:- Faculty
- Staff
- Students
When can I use it?
Example:
This service is available all the timeYou can use this application anytime.
How much does it cost?
Example:
This service is available at no charge to the KU community.
How do I get it?
You can install Jupyter Notebook by following the steps in the link below:
How can I use it?
Jupyter notebooks can be used to communicate and share materials for learning and teaching, as well as research outputs. For example:
- Share a Jupyter Notebook with instructional materials and exercises to support students learning to code. (Example link: ARC Lessons - Introduction to Programming in Python)
- Jupyter Notebook simulations to allow students to explore a problem: a coding to learn approach.
- Jupyter Notebooks is a lab book of data analysis, which includes code, results, and discussion. This could support student project work or research as a supplement for to a lab report. (Example link: student project - The Bayesian Astrometric Dust Cartogropher)
Useful links
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