Project Jupyter
NumFOCUS Sponsored Project since 2014Project Jupyter develops tools for interactive computing, research and education with an emphasis in data science workflows. Its flagship application is the widely used Jupyter Notebook, a web application that allows users to craft live narratives combining text, code and multimedia output. These documents support exploratory computing in a wide array of programming languages and can be shared to support collaborative and reproducible work.
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Industry
Business & Industry Applications
Higher Education Research & Teaching
Language
Python
R
Julia
JavaScript
and 50–100 other languages
Features
Data Wrangling
Modeling
Visualization
High Performance Computing
Big Data
Statistical Computing
Numerical Computing
Data Mining
Text Processing
Machine Learning
Computing Language
Educational Outreach
Computational thinking
Version control
Several companies have released Jupyter-based products, including Google (Cloud DataLab), Microsoft (AzureML, HDInsight), IBM (IBM Watson Studio), and Intel (Trusted Analytics Platform). It is used in Anaconda Enterprise and Conda, and Netflix uses Jupyter internally. Quantopian has hosted notebooks for financial modeling. It is also in use at the NBA and Bloomberg.
Jupyter is used in educational materials at Software and Data Carpentries and is used in courses at many universities including: Bryn Mawr College, Cal Poly, Clemson University, George Washington University, Michigan State University, New York University, Northwestern University, UC Berkeley, and University of Sheffield.
Brookhaven National Laboratory uses Jupyter in analysis of data from scientific instruments (light sources). NASA uses it for data analysis and internally uses nbviewer for collaboration. Lawrence Berkeley National Laboratory uses Jupyter in multiple scientific projects, including KBase and a Materials Project.
Traditional published books have been written using notebooks or ship the code that accompanies the books as notebooks, such as at O’Reilly Media. News organizations are writing data-driven news articles for the traditional consumer market and sharing their code and data from those articles as notebooks.