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  1. NumPy

    Nearly every scientist working in Python draws on the power of NumPy. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to …

  2. NumPy - Wikipedia

    NumPy (pronounced / ˈnʌmpaɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection …

  3. numpy · PyPI

    NumPy is a community-driven open source project developed by a diverse group of contributors. The NumPy leadership has made a strong commitment to creating an open, inclusive, and …

  4. GitHub - numpy/numpy: The fundamental package for scientific …

    NumPy is a community-driven open source project developed by a diverse group of contributors. The NumPy leadership has made a strong commitment to creating an open, inclusive, and …

  5. NumPy Tutorial - Python Library - GeeksforGeeks

    Nov 27, 2025 · NumPy is a core Python library for numerical computing, built for handling large arrays and matrices efficiently. It is significantly faster than Python's built-in lists because it …

  6. NumPy Tutorial - W3Schools

    NumPy is a Python library. NumPy is used for working with arrays. NumPy is short for "Numerical Python".

  7. NumPy Tutorials [Beginners to Advanced Level] - Python Guides

    NumPy, short for Numerical Python, is a fundamental library in Python used for scientific computing. It provides support for large, multi-dimensional arrays and matrices, along with a …

  8. NumPy documentation — NumPy v1.26 Manual

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

  9. SciPy

    Extends NumPy providing additional tools for array computing and provides specialized data structures, such as sparse matrices and k-dimensional trees.

  10. NumPy - Installing NumPy

    The only prerequisite for installing NumPy is Python itself. If you don’t have Python yet and want the simplest way to get started, we recommend you use the Anaconda Distribution - it includes …