NumPy documentation - Numpy

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################### NumPy documentation ###################

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User Guide <user/index> API reference <reference/index> Building from source <building/index> Development <dev/index> release

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Download documentation: Historical versions of documentation <https://numpy.org/doc/>_

Useful links: Home <https://numpy.org>_ | Installation <https://numpy.org/install/>_ | Source Repository <https://github.com/numpy/numpy>_ | Issue Tracker <https://github.com/numpy/numpy/issues>_ | Q&A Support <https://numpy.org/gethelp/>_ | Mailing List <https://mail.python.org/mailman/listinfo/numpy-discussion>_

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.

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    Getting started
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    New to NumPy? Check out the Absolute Beginner's Guide. It contains an
    introduction to NumPy's main concepts and links to additional tutorials.

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        To the absolute beginner's guide

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    User guide
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    The user guide provides in-depth information on the
    key concepts of NumPy with useful background information and explanation.

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    API reference
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    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.

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    Contributor's guide
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    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.

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