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.
Jupyter notebooks are a series of “cells” containing executable code, or markdown, the popular HTML markup language for prose descriptions. They have LaTeX support for mathematical equations with MathJax.
The notebook’s 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 many 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.
- Highly customizable.
- 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.
- Author narrative text using the Markdown markup language.
- The ability to easily include mathematical notation within markdown cells using LaTeX, and rendered natively by MathJax.
- Notebooks can be committed to version control repositories such as git and the code sharing site GitHub.
- Export notebooks to HTML, reStructuredText, LaTeX, PDF, and slide shows.
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.
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