The Notebook has support for over 40 programming languages, including those popular in Data Science such as Python, R, Julia and Scala.
Notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer.
Leverage big data tools, such as Apache Spark, from Python, R and Scala. Explore that same data with pandas, scikit-learn, ggplot2, dplyr, etc.
A multi-user version of the notebook designed for companies, classrooms and research labs
Manage users and authentication with PAM, OAuth or integrate with your own directory service system. Collaborate with others through the Linux permission model.
Deploy the Jupyter Notebook to all of the users in your organization on centralized servers on- or off-site.
Use Docker containers to scale your deployment and isolate user processes using a growing ecosystem of prebuilt Docker containers.
Deploy the Notebook next to your data to provide unified software management and data access within your organization.