Description

Jupyter Notebooks allow users to create computational narratives that combine live code, equations, explanatory text, and interactive user interfaces. These open-source tools support scientific computing and data science in a number of programming languages including Python, R, and Julia.

Demonstration video

Link to a short (5 minute) demonstration of the key features of the tool or service.

Primary features

• Enables sharing of documents that contain live code, equations, visualizations and explanatory text.
• Notebooks can be shared using Github, Dropbox, email, or the Jupyter Notebook Viewer

Example use cases

Short description of example use cases and links to relevant installations if appropriate.

• Jupyter Notebooks have been integrated with Clowder for the TERRA-REF project.

See also

• Project Jupyter: Computational Narratives as the Engine of Collaborative Data Science
• Jupyter Documentation

In Labs Workbench

The following Jupyter tools are available in Labs Workbench:

• Jupyter Data Science Notebook

• Jupyter Minimal Notebook

• Jupyter Lab Alpha

NOTE: The following services generate a password in their log files on startup:

• Jupyter Data Science Notebook
• Jupyter Minimal Notebook

This is in addition to allowing the user to specify basic-auth with their Workbench credentials.

Simply copy and paste this password when Jupyter prompts you