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-NumPy is the fundamental package needed for scientific computing with Python.  It contains among other things:
-
-- 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. 
-
-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.
-
-Getting Started
----------------
-
-- `Getting Numpy <http://www.scipy.org/Download>`_
-- `Installing NumPy and SciPy <http://www.scipy.org/Installing_SciPy>`_
-- `NumPy and SciPy documentation page <http://docs.scipy.org/doc/>`_
-- `NumPy Tutorial <http://www.scipy.org/Tentative_NumPy_Tutorial>`_
-- `NumPy for MATLAB© Users <http://www.scipy.org/NumPy_for_Matlab_Users>`_
-- `NumPy functions by category <http://www.scipy.org/Numpy_Functions_by_Category>`_
-- `NumPy Mailing List <http://www.scipy.org/Mailing_Lists>`_
-
-More Information
-----------------
-
-- `NumPy Sourceforge Home Page <http://sourceforge.net/projects/numpy/>`_
-- `SciPy Home Page <http://www.scipy.org/>`_
-- `Interfacing with compiled code <http://www.scipy.org/Topical_Software#head-7153b42ac4ea517c7d99ec4f4453555b2302a1f8>`_
-- :doc:`Older python array packages </old_array_packages>`
-
-.. toctree::
-   :hidden:
-
-   old_array_packages