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<!DOCTYPE html>

<head>

<title>NumPy documentation — NumPy v2.5.dev0 Manual</title>

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DOCUMENTATION_OPTIONS.theme_version = '0.16.1';

DOCUMENTATION_OPTIONS.theme_switcher_json_url = 'https://numpy.org/doc/_static/versions.json';

DOCUMENTATION_OPTIONS.theme_switcher_version_match = 'devdocs';

DOCUMENTATION_OPTIONS.show_version_warning_banner =

true;

</script>

</head>

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User Guide

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</li>

API reference

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Building from source

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Development

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Release notes

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Learn

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User Guide

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Building from source

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<span id="numpy-docs-mainpage"></span><h1>NumPy documentation<a class="headerlink" href="#numpy-documentation" title="Link to this heading">#</a></h1>

</div>

<p><strong>Version</strong>: 2.5.dev0</p>

<p><strong>Download documentation</strong>:

<a class="reference external" href="https://numpy.org/doc/">Historical versions of documentation</a></p>

<p><strong>Useful links</strong>:

<a class="reference external" href="https://numpy.org">Home</a> |

<a class="reference external" href="https://numpy.org/install/">Installation</a> |

<a class="reference external" href="https://github.com/numpy/numpy">Source Repository</a> |

<a class="reference external" href="https://github.com/numpy/numpy/issues">Issue Tracker</a> |

<a class="reference external" href="https://numpy.org/gethelp/">Q&A Support</a> |

<a class="reference external" href="https://mail.python.org/mailman/listinfo/numpy-discussion">Mailing List</a></p>

<p>NumPy is the fundamental package for scientific computing in Python. It is a

Python library that provides a multidimensional array object, various derived

objects (such as masked arrays and matrices), and an assortment of routines for

fast operations on arrays, including mathematical, logical, shape manipulation,

sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra,

basic statistical operations, random simulation and much more.</p>

<p class="sd-card-text">Getting started</p>

</div>

<p class="sd-card-text">New to NumPy? Check out the Absolute Beginner’s Guide. It contains an

introduction to NumPy’s main concepts and links to additional tutorials.</p>

</div>

<p class="sd-card-text"><span class="sd-d-grid"><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-secondary sd-stretched-link reference internal" href="user/absolute_beginners.html"><span class="doc">To the absolute beginner’s guide</span></a></span></p>

</div>

<p class="sd-card-text">User guide</p>

</div>

<p class="sd-card-text">The user guide provides in-depth information on the

key concepts of NumPy with useful background information and explanation.</p>

</div>

<p class="sd-card-text"><span class="sd-d-grid"><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-secondary sd-stretched-link reference internal" href="user/index.html#user"><span class="std std-ref">To the user guide</span></a></span></p>

</div>

<p class="sd-card-text">API reference</p>

</div>

<p class="sd-card-text">The reference guide contains a detailed description of the functions,

modules, and objects included in NumPy. The reference describes how the

methods work and which parameters can be used. It assumes that you have an

understanding of the key concepts.</p>

</div>

<p class="sd-card-text"><span class="sd-d-grid"><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-secondary sd-stretched-link reference internal" href="reference/index.html#reference"><span class="std std-ref">To the reference guide</span></a></span></p>

</div>

<p class="sd-card-text">Contributor’s guide</p>

</div>

<p class="sd-card-text">Want to add to the codebase? Can help add translation or a flowchart to the

documentation? The contributing guidelines will guide you through the

process of improving NumPy.</p>

</div>

<p class="sd-card-text"><span class="sd-d-grid"><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-secondary sd-stretched-link reference internal" href="dev/index.html#devindex"><span class="std std-ref">To the contributor’s guide</span></a></span></p>

</div>

</section>

</article>

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