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  1. NumPy documentation — NumPy v2.3 Manual

    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 …

  2. NumPy user guide — NumPy v2.3 Manual

    NumPy user guide # This guide is an overview and explains the important features; details are found in NumPy reference.

  3. Overview — NumPy v1.21 Manual

    Jun 22, 2021 · Large parts of this manual originate from Travis E. Oliphant's book "Guide to NumPy" (which generously entered public domain in August 2008). The reference …

  4. NumPy quickstart — NumPy v2.5.dev0 Manual

    NumPy’s main object is the homogeneous multidimensional array. It is a table of elements (usually numbers), all of the same type, indexed by a tuple of non-negative integers.

  5. NumPy: the absolute basics for beginners — NumPy v2.2 Manual

    The NumPy library contains multidimensional array data structures, such as the homogeneous, N-dimensional ndarray, and a large library of functions that operate efficiently on these data …

  6. Constants — NumPy v2.3 Manual

    Notes NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not …

  7. NumPy reference — NumPy v2.3 Manual

    Jun 9, 2025 · This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see the complete …

  8. NumPy fundamentals — NumPy v2.3 Manual

    These documents clarify concepts, design decisions, and technical constraints in NumPy. This is a great place to understand the fundamental NumPy ideas and philosophy.

  9. NumPy - News

    Dec 8, 2024 · July 12, 2021 – At NumPy, we believe in the power of our community. 1,236 NumPy users from 75 countries participated in our inaugural survey last year. The survey findings …

  10. numpy.where — NumPy v2.3 Manual

    numpy.where # numpy.where(condition, [x, y, ]/) # Return elements chosen from x or y depending on condition.