# NumPy [![Travis](https://img.shields.io/travis/numpy/numpy/master.svg?label=Travis%20CI)](https://travis-ci.org/numpy/numpy) [![AppVeyor](https://img.shields.io/appveyor/ci/charris/numpy/master.svg?label=AppVeyor)](https://ci.appveyor.com/project/charris/numpy) NumPy is the fundamental package needed for scientific computing with Python. - **Website (including documentation):** http://www.numpy.org - **Mailing list:** https://mail.python.org/mailman/listinfo/numpy-discussion - **Source:** https://github.com/numpy/numpy - **Bug reports:** https://github.com/numpy/numpy/issues It provides: - a powerful N-dimensional array object - sophisticated (broadcasting) functions - tools for integrating C/C++ and Fortran code - useful linear algebra, Fourier transform, and random number capabilities If ``nose`` is installed, tests can be run after installation with: python -c 'import numpy; numpy.test()' [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)