|
- 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 - 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 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
- What is NumPy? — NumPy v2. 3 Manual
What is NumPy? # NumPy is the fundamental package for scientific computing in Python
- 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 equivalent to negative infinity But infinity is equivalent to positive infinity Examples Try it in your browser!
- Indexing on ndarrays — NumPy v2. 3 Manual
The native NumPy indexing type is intp and may differ from the default integer array type intp is the smallest data type sufficient to safely index any array; for advanced indexing it may be faster than other types
|
|
|