Jupyter Notebooks

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. The notebooks can be used for data cleaning and transformation, numerical analysis, statistical modeling, data visualization, machine learning and much more.

Jupyter Notebook supports data based ad-hoc discovery efforts and analysis with analytics libraries and rich visualizations to quickly analyze for patterns, anomalies and predictions, share it amongst team as first steps in operationalizing insights.

• Supported Languages:  Jupyter supports over 40 programming languages, including Python, R and Scala. 
• Discover & Share: Notebooks can be shared with others using email, Dropbox, GitHub.
• Interactive Output: supports data and statistical analysis all allows  to code can produce rich, interactive output: HTML, images, videos, LaTeX, and custom MIME types
• Integration: Leverage big data tools, such as Apache Spark, from Python, R and Scala. 

The Jupyter notebook  can be presented over a web browser and the architecture is based on a server-client structure. The notebook server uses an extensible  kernel architecture  based on ZeroMQ with Tornado for serving HTTP requests. Notebook server runs the language kernel and communicates with the front-end Notebook client

The Notebook server runs on Linux operating system – CentOS 7.x, RedHat 7.x. The web user interface works with all modern browsers including Google Chrome, Mozilla Firefox and Microsoft Edge and is able to perform analytical operations through supported languages and included libraries.