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- 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
- 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 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
- 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!
- Data types — NumPy v2. 3 Manual
NumPy numerical types are instances of numpy dtype (data-type) objects, each having unique characteristics Once you have imported NumPy using import numpy as np you can create arrays with a specified dtype using the scalar types in the numpy top-level API, e g numpy bool, numpy float32, etc
- 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
- Broadcasting — NumPy v2. 3 Manual
The term broadcasting describes how NumPy treats arrays with different shapes during arithmetic operations Subject to certain constraints, the smaller array is “broadcast” across the larger array so that they have compatible shapes
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