OSS Business Incubator

NumPy is an open source project aiming to enable numerical computing with Python. It was created in 2005, building on the early work of the Numeric and Numarray libraries. NumPy will always be 100% open source software, free for all to use and released under the liberal terms of the modified BSD license. NumPy is developed in the open on GitHub, through the consensus of the NumPy and wider scientific Python community. For more information on our governance approach, please see our Governance Document.

We are building XND to recreate the foundations of NumPy as a number of smaller libraries, combining the lessons learned in the past twenty years of array computing in Python with the needs of newer applications. This is not a replacement of NumPy. Eventually, NumPy could use XND as could Pandas, Dask, and other libraries. In fact, we are actively working on using XND in Numba and are also very interested in integrating it with other libraries.

HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple. With HoloViews, you can usually express what you want to do in very few lines of code.

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool.

Web application RPC library for Clojure/Script and Ring. It has great features. 

PyData is an educational program of NumFOCUS, a 501(c)(3) nonprofit charity.

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.

Blosc is a rapid binary data compressor that optimizes fetching data to the processor cache, outperforming traditional memory access methods. It reduces large datasets on disk or in memory and accelerates memory-intensive tasks like vector operations. 

Package, dependency and environment management for any language—Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN, and more. Conda is an open source package management system and environment management system that runs on Windows, macOS and Linux. Conda quickly installs, runs and updates packages and their dependencies. Conda easily creates, saves, loads and switches between environments on your local computer. It was created for Python programs

DyND is a C++ library for dynamic, multidimensional arrays. It is inspired by NumPy, the Python array programming library at the core of the scientific Python stack, but tries to address a number of obstacles encountered by some of its users. Examples of this are support for variable-sized string, ragged array types, and convenient usage from C++. The library is in a preview development state, and can be thought of as a sandbox.

Ibis is a toolbox to bridge the gap between local Python environments (like pandas and scikit-learn) and remote storage and execution systems like Hadoop components (like HDFS, Impala, Hive, Spark) and SQL databases (Postgres, etc.). Its goal is to simplify analytical workflows and make you more productive.

SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.

QHub enables teams to build and maintain a cost-effective and scalable compute/data science platform in the cloud or on-premises. 

Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing.

DataShape is a language for describing data. It is an extension of the NumPy dtype with an emphasis on cross language support.

A powerful interactive shell. A kernel for Jupyter. Support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.

High-level tools to simplify visualization in Python.

Simple and efficient tools for predictive data analysis · Accessible to everybody, and reusable in various contexts · Built on NumPy, SciPy, and matplotlib. This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started work on this project as part of his thesis. In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. 

Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite, and the source is available on GitHub. With Altair, you can spend more time understanding your data and its meaning. Altair’s API is simple, friendly and consistent and built on top of the powerful Vega-Lite visualization grammar. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code.

Bokeh is a Python library for creating interactive visualizations for modern web browsers. It helps you build beautiful graphics, ranging from simple plots to complex dashboards with streaming datasets. With Bokeh, you can create JavaScript-powered visualizations without writing any JavaScript yourself.

An open source machine learning framework that accelerates the path from research prototyping to production deployment. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

A community-led collection of recipes, build infrastructure and distributions for the conda package manager.

A a free open-source video conferencing software for web & mobile