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- 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 learn and use
- 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 Python, NumPy, and many other commonly used packages for scientific computing and data science
- NumPy Documentation
NumPy 1 20 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy 1 19 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy 1 18 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy 1 17 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy 1 16 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy
- 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
- What is NumPy? — NumPy v2. 3 Manual
What is NumPy? # NumPy is the fundamental package for scientific computing in Python
- numpy. where — NumPy v2. 3 Manual
numpy where # numpy where(condition, [x, y, ] ) # Return elements chosen from x or y depending on condition
- NumPy quickstart — NumPy v2. 4. 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
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