Jupyter Notebooks
- Craig Willis
- Sara Lambert
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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:
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