About NumPy =========== `NumPy <http://www.scipy.org/NumpPy/>`__ is the fundamental package needed for scientific computing with Python. This package contains: - a powerful N-dimensional :ref:`array object <arrays>` - sophisticated :ref:`(broadcasting) functions <ufuncs>` - basic :ref:`linear algebra functions <routines.linalg>` - basic :ref:`Fourier transforms <routines.fft>` - sophisticated :ref:`random number capabilities <routines.random>` - tools for integrating Fortran code - tools for integrating C/C++ code Besides its obvious scientific uses, *NumPy* can also be used as an efficient multi-dimensional container of generic data. Arbitrary data types can be defined. This allows *NumPy* to seamlessly and speedily integrate with a wide variety of databases. NumPy is a successor for two earlier scientific Python libraries: NumPy derives from the old *Numeric* code base and can be used as a replacement for *Numeric*. It also adds the features introduced by *Numarray* and can also be used to replace *Numarray*. NumPy community --------------- NumPy is a distributed, volunteer, open-source project. *You* can help us make it better; if you believe something should be improved either in functionality or in documentation, don't hesitate to contact us --- or even better, contact us and participate in fixing the problem. Our main means of communication are: - `scipy.org website <http://scipy.org/>`__ - `Mailing lists <http://scipy.org/Mailing_Lists>`__ - `NumPy Issues <https://github.com/numpy/numpy/issues>`__ (bug reports go here) - `Old NumPy Trac <http://projects.scipy.org/numpy>`__ (no longer used) More information about the development of NumPy can be found at our `Developer Zone <https://scipy.scipy.org/scipylib/dev-zone.html>`__. If you want to fix issues in this documentation, the easiest way is to participate in `our ongoing documentation marathon <http://scipy.org/Developer_Zone/DocMarathon2008>`__. About this documentation ======================== Conventions ----------- Names of classes, objects, constants, etc. are given in **boldface** font. Often they are also links to a more detailed documentation of the referred object. This manual contains many examples of use, usually prefixed with the Python prompt ``>>>`` (which is not a part of the example code). The examples assume that you have first entered:: >>> import numpy as np before running the examples.