NumPy Cookbook - Second Edition
Format:
Paperback
En stock
0.45 kg
Sí
Nuevo
Amazon
USA
- Over 90 fascinating recipes to learn and perform mathematical, scientific, and engineering Python computations with NumPyAbout This BookPerform high-performance calculations with clean and efficient NumPy codeSimplify large data sets by analysing them with statistical functionsA solution-based guide packed with engaging recipes to execute complex linear algebra and mathematical computationsWho This Book Is ForIf you are a Python developer with some experience of working on scientific, mathematical, and statistical applications and want to gain an expert understanding of NumPy programming in relation to science, math, and finance using practical recipes, then this book is for you.What You Will LearnLearn advanced indexing and linear algebraDeal with missing stock price data using masked arraysExplore everything you need to know about image processingDive into broadcasting and histogramsProfile NumPy code and visualize the resultsSpeed up your code with CythonUse universal functions and interoperability featuresAnalyze your performance using Quality AssuranceLearn about exploratory and predictive data analysis with NumPyIn DetailNumPy has the ability to give you speed and high productivity. High performance calculations can be done easily with clean and efficient code, and it allows you to execute complex algebraic and mathematical computations in no time.This book will give you a solid foundation in NumPy arrays and universal functions. Starting with the installation and configuration of IPython, you'll learn about advanced indexing and array concepts along with commonly used yet effective functions. You will then cover practical concepts such as image processing, special arrays, and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project with the help of examples. At the end of the book, you will study how to explore atmospheric pressure and its related techniques. By the time you finish this book, you'll be able to write clean and fast code with NumPy.
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