An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library
Overview
- Perform high performance calculations with clean and efficient NumPy code
- Analyze large data sets with statistical functions
- Execute complex linear algebra and mathematical computations
In Detail
NumPy is an extension to, and the fundamental package for scientific computing with Python. In today's world of science and technology, it is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list.
NumPy Beginner's Guide will teach you about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, is free and open source.
Write readable, efficient, and fast code, which is as close to the language of mathematics as is currently possible with the cutting edge open source NumPy software library. Learn all the ins and outs of NumPy that requires you to know basic Python only. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favourite programming language.You will learn about installing and using NumPy and related concepts. At the end of the book we will explore some related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. Through examples, you will also learn about plotting with Matplotlib and the related SciPy project. NumPy Beginner's Guide will help you be productive with NumPy and have you writing clean and fast code in no time at all.
What you will learn from this book
- Install NumPy
- NumPy arrays
- Universal functions
- NumPy matrices
- NumPy modules
- Plot with Matplotlib
- Test NumPy code
- Relation to SciPy
Approach
The book is written in beginner’s guide style with each aspect of NumPy demonstrated with real world examples and required screenshots.
Who this book is written for
If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.
An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library
Overview
- Perform high performance calculations with clean and efficient NumPy code
- Analyze large data sets with statistical functions
- Execute complex linear algebra and mathematical computations
In Detail
NumPy is an extension to, and the fundamental package for scientific computing with Python. In today's world of science and technology, it is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list.
NumPy Beginner's Guide will teach you about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, is free and open source.
Write readable, efficient, and fast code, which is as close to the language of mathematics as is currently possible with the cutting edge open source NumPy software library. Learn all the ins and outs of NumPy that requires you to know basic Python only. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favourite programming language.You will learn about installing and using NumPy and related concepts. At the end of the book we will explore some related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. Through examples, you will also learn about plotting with Matplotlib and the related SciPy project. NumPy Beginner's Guide will help you be productive with NumPy and have you writing clean and fast code in no time at all.
What you will learn from this book
- Install NumPy
- NumPy arrays
- Universal functions
- NumPy matrices
- NumPy modules
- Plot with Matplotlib
- Test NumPy code
- Relation to SciPy
Approach
The book is written in beginner’s guide style with each aspect of NumPy demonstrated with real world examples and required screenshots.
Who this book is written for
If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.
