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- NumPy
NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use With this power comes simplicity: a solution in NumPy is often clear and elegant
- NumPy - Learn
Why NumPy? Powerful n-dimensional arrays Numerical computing tools Interoperable Performant Open source
- NumPy
O NumPy oferece um conjunto completo de funções matemáticas, geradores de números aleatórios, rotinas de álgebra linear, transformadas de Fourier, e mais
- NumPy quickstart — NumPy v2. 3 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
- What is NumPy? — NumPy v2. 3 Manual
NumPy arrays facilitate advanced mathematical and other types of operations on large numbers of data Typically, such operations are executed more efficiently and with less code than is possible using Python’s built-in sequences
- NumPy - Installing NumPy
The recommended method of installing NumPy depends on your preferred workflow Below, we break down the installation methods into the following categories: Project-based (e g , uv, pixi) (recommended for new users) Environment-based (e g , pip, conda) (the traditional workflow) System package managers (not recommended for most users)
- NumPy Documentation
NumPy Enhancement Proposals Versions: Numpy 2 3 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 2 2 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 2 1 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 2 0 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 1 26 Manual [HTML+zip] Numpy 1 25
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