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NumPy Beginner's Guide

NumPy Beginner's Guide

By : Ivan Idris
4.2 (14)
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NumPy Beginner's Guide

NumPy Beginner's Guide

4.2 (14)
By: Ivan Idris

Overview of this book

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.
Table of Contents (19 chapters)
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Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


This chapter was about Matplotlib—a Python plotting library. We covered simple plots, histograms, plot customization, subplots, 3D plots, contour plots, and logplots. We also saw a few examples of displaying stock charts. Obviously, we only scratched the surface and saw the tip of the iceberg. Matplotlib is very feature rich, so we didn’t have space to cover LaTex support, polar coordinates support, and other functionality.

The author of Matplotlib, John Hunter, passed away in August, 2012. One of the technical reviewers of this book suggested mentioning the John Hunter Memorial Fund (http://numfocus.org/johnhunter/). The memorial fund set up by the NumFocus Foundation is an opportunity for us, as fans of John Hunter’s work, to "give back" so to say. Again, for more details, check out the previous link to the NumFocus website.

The next chapter is about SciPy—a scientific Python framework that is built on top of NumPy.

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