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- NumPy - Learn
Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community
- 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 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
What is NumPy? # NumPy is the fundamental package for scientific computing in Python
- NumPy Documentation
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 1 15 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] NumPy
- 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
- Mathematical functions — NumPy v2. 4 Manual
Handling complex numbers # Extrema finding # Miscellaneous # previous numpy not_equal next numpy sin
- numpy. where — NumPy v2. 3 Manual
numpy where # numpy where(condition, [x, y, ] ) # Return elements chosen from x or y depending on condition
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