Open source, interactive data science and scientific computing across over 40 programming languages.
The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.
The Notebook has support for over 40 programming languages, including those popular in Data Science such as Python, R, Julia and Scala.
Leverage big data tools, such as Apache Spark, from Python, R and Scala. Explore that same data with pandas, scikit-learn, ggplot2, dplyr, etc.
JupyterHub is a multiuser version of the notebook designed for centralized deployments in companies, university 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 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.
The Jupyter Notebook is based on a set of open standards for interactive computing. Think HTML and CSS for interactive computing on the web. These open standards can be leveraged by third party developers to build customized applications with embedded interactive computing.