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<h1>NumPy<a class="headerlink" href="#numpy" title="Permalink to this headline">¶</a></h1>
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<p>NumPy is the fundamental package for scientific computing with Python.
It contains among other things:</p>
<ul class="simple">
<li>a powerful N-dimensional array object</li>
<li>sophisticated (broadcasting) functions</li>
<li>tools for integrating C/C++ and Fortran code</li>
<li>useful linear algebra, Fourier transform, and random number capabilities</li>
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<p>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
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<p>NumPy is licensed under the <a class="reference internal" href="license.html#license"><span class="std std-ref">BSD license</span></a>, enabling reuse with
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<h2>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this headline">¶</a></h2>
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<li><a class="reference external" href="http://www.scipy.org/scipylib/download.html">Getting NumPy</a></li>
<li><a class="reference external" href="http://www.scipy.org/install.html">Installing the SciPy Stack</a></li>
<li><a class="reference external" href="http://docs.scipy.org/doc/">NumPy and SciPy documentation page</a></li>
<li><a class="reference external" href="https://docs.scipy.org/doc/numpy-dev/user/quickstart.html">NumPy Tutorial</a></li>
<li><a class="reference external" href="https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html">NumPy for MATLAB© Users</a></li>
<li><a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/routines.html">NumPy functions by category</a></li>
<li><a class="reference external" href="http://www.scipy.org/scipylib/mailing-lists.html">NumPy Mailing List</a></li>
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<p>For more information on the SciPy Stack (for which NumPy provides the
fundamental array data structure), see <a class="reference external" href="http://www.scipy.org/">scipy.org</a>.</p>
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