5 Best Open Source Multi-Platform Data Science Notebook Software

Jupyter Notebook

The Jupyter Notebook is an open-source server-client web application that allows you to create and share documents containing live code, equations, visualizations and explanatory text.  Its two main components are its kernels and a dashboard. A kernel runs and introspects the user’s code. The Jupyter Notebook App has a kernel for Python code, but there are also kernels available for other programming languages.

Jupyter Notebook installs the IPython kernel. This allows working on notebooks using the Python programming language.

Uses include data cleaning and transformation, numerical simulation, statistical modeling, machine learning and a lot more.

Features include:

• Support for over 40 programming languages, including those popular in Data Science such as Python, R, Julia, and Scala
• In-browser editing for code, using the Markdown markup language, with automatic syntax highlighting, indentation, and tab completion/introspection
• Execute code from the browser, with the results of computations attached to the code which generated them
• Display the result of computation using rich media representations, such as HTML, LaTeX, PNG, SVG, etc. For example, render publication-quality figures inline with the matplotlib library
• The ability to easily include mathematical notation within markdown cells using LaTeX, and rendered natively by MathJax
• Export notebooks to HTML, reStructuredText, LaTeX, PDF, and slide shows

OS	Supported	Notes
		Jupyter runs code in many programming languages, Python is a requirement (Python 3.3 or greater, or Python 2.7). Installing Acaconda is the recommended installation method. Homepage: jupyter.org Developer: Many License: Modified BSD license Written in: Python

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