NumPy Beginner's Guide - Second Edition 2nd Revised ed. Edition

by Ivan Idris (Author)

14 ratings

ISBN-13: 978-1782166085

ISBN-10: 1782166084

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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 beginners 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.

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Product details

Publisher ‏ : ‎ Packt Publishing; 2nd Revised ed. edition (April 25, 2013)
Language ‏ : ‎ English
Paperback ‏ : ‎ 310 pages
ISBN-10 ‏ : ‎ 1782166084
ISBN-13 ‏ : ‎ 978-1782166085
Item Weight ‏ : ‎ 1.18 pounds
Dimensions ‏ : ‎ 7.5 x 0.7 x 9.25 inches

Best Sellers Rank: #3,961,497 in Books (See Top 100 in Books)
- #1,659 in Mathematical & Statistical Software
- #3,975 in Python Programming
- #5,652 in Web Design (Books)

Customer Reviews:
14 ratings

About the author

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Ivan Idris

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Ivan Idris was born in Bulgaria from Indonesian parents. He moved to the Netherlands in the 1990s, where he graduated from high school and got a MSc in Experimental Physics.

His graduation thesis had a strong emphasis on Applied Computer Science. After graduating he worked for several companies as Java Developer, Datawarehouse Developer and QA Analyst.

His main professional interests are Business Intelligence, Big Data and Cloud Computing. Ivan Idris enjoys writing clean testable code and interesting technical articles.

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Kelly Summerlin

5 stars for material, 3 for presentation

Reviewed in the United States on July 10, 2013

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The material covered is pretty good considering the breadth of the NumPy library. I would have like more coverage of the NumPy record types. The only real problem I had with this book, I wasn't happy with the style of the material presented. The style tries to present a problem to solve with NumPy, then shows a segment of programming steps to solve the problem, and finally shows the completed code. I think I prefer the cookbook style of O'Reilly books better.

This style almost presents the solution twice once with a step by step, and then again with full code. It seems redundant.

6 people found this helpful

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Bayview

Four Stars

Reviewed in the United States on October 3, 2014

Happy with purchase.

Reviewed in the United States on October 4, 2014

Verified Purchase

Nice coverage of the numpy library

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Amit Saha

Interestingly written, but needs serious editing polish

Reviewed in the United States on May 7, 2013

I received a review copy of Packt Publishing's NumPy Beginners Guide by Ivan Idris. The book looks into using the NumPy library for numerical computing in Python. Here is my review.

(The book uses Python 2).

Chapters

The book has 11 chapters. The book starts with a bit of history about NumPy and the first seven chapters look into various NumPy functions for array and matrix manipulation, linear algebra specific functions, statistical and financial calculations and others. Chapter 8 looks into unit testing your programs, followed by chapter 9 which looks into plotting with matplotlib. Chapter 10 discusses SciPy and the last chapter discusses PyGame and how to integrate it with SciPy and NumPy to implement cool-looking games.

Each chapter also has sections titled "Time for Action" and "What just happened?" with the former discussing a practical programming solution and the latter discussing it.

Interesting Features

Hands-on style
Pop quizzes are a fun addition
"What just happened?" explaining the "Time for Action" is interesting.

Source code

The book has lots of code. The code examples are short and mostly easy to follow and well explained most of the times. I didn't sit on my computer and type the codes, so don't know if there are any non-functioning codes.

Summary

The book is interesting and it does well in introducing features of NumPy using real life examples, instead of simply stating what a function does. However, depending on the reader, the examples can range from difficult to alien which will make the reader skim through those pages. The author does a good job, but book needs serious editing polish.

2 people found this helpful

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JGM

About "NumPy Beginner's Guide" (2nd Edition)

Reviewed in the United States on June 30, 2013

When one is dealing with numerical methods, there are many good reasons to do so using free/open numerical tools ... But, whether you happen to be doing "real" work for a company or to be a PhD candidate, too often you are confronted with the dilemma of investing your time in learning alternative and more productive ways of doing your work (i.e. the promising combination python/NumPy) and actually having your work done by the due date.

As a PhD student myself, article reviewing, code debugging, data analysis and other obligations and deadlines have been so far the reason not to get the grips with NumPy ... until I found Mr. Idris's "NumPy - Beginner's guide"!

Personally, I find the most remarkable feature of the book to be the good compromise the author has found between:
* the amount and relevance of the information offered,
* the clarity of the exposition and
* the immediate applicability of the information provided.

As a first remark, the book covers many of the most recurrent techniques I need to use during my research activity, and thus the book can very well serve as a reference. However, do not mistake the book as yet another "How To" guide, or a simple "Cook-Book": far from that, you see an evident and conscious effort to lead the reader through different capabilities of NumPy in a bottom-up, constructive manner: this is a book you can actually learn from.

Another highlight of the book is the early focus on data processing from text files. Instead of presenting this feature in an arcane manner detached from other features (as is often the case in many programming guides), the author presents briefly but in enough detail the text-file-processing capabilities of NumPy intertwined with several statistical analysis tools.

Of course, there is a space devoted to most common procedures for linear algebra, signal processing, efficient sorting algorithms, ...

Yet another success of the book concerns the graphical representation of information; the book devotes a full chapter to matplotlib and to explain how to produce the most common graphs needed to effectively communicate one's work . This does not prevent the author to use matplotlib if needed in previous chapters, offering in any of such occasions at least the minimal explanation of what is being done.

To conclude, I believe this book can help users/developers of numerical methods to become independent and proficient users of NumPy: a reader minimally familiar with the python syntax will be able, in very short time, to port her/his existing numerical tools into NumPy, thus acquiring the experience needed to devise new, more efficient tools taking advantage of the advantages of the python/NumPy duo.

18 people found this helpful

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Schnack

Guter Einstieg, wenn auch nicht perfekt

Reviewed in Germany on December 5, 2013

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Aus Interesse und beruflichen Gründen habe ich vor kurzer Zeit damit begonnen Python zu lernen, vor allem mit Hinlbick auf NumPy und SciPy. Ich hatte rudimentäre Programmiervorkenntnisse und war bereits mit R für statistische Auswertungen und Matrizenrechnungen vertraut. Daher war der Einstieg in NumPy für mich recht einfach. Das wichtigste bei NumPy ist zu verstehen, dass nahezu alles über Arrays funktioniert. Hier hat das Buch "NumPy Beginner's Guide - Second Edition " mich nur teilweise überzeugt. Zwar wird die Idee der Arrays gut eingeführt, aber eben nicht vollstänidg aus meiner Sicht. Etliche Dinge, z.T. eigentlich triviale Sachen, musste mir über das Internet aneignen. Der Rest des Buches sind größtenteils Beispiele aus verschiedenen Wisschenschaftsbereichen, um bestimmte eingebaute Funktionen zu erläutern. Ich finde das durchaus in Ordnung, jedoch bleibt vieles davon für den Einzelnen unbrauchbar. So sind z.B. sämtliche Beispiele aus dem Bereich Wirtschaft für mich garnicht nützlich gewesen.

Mein Rat ist folgender: Wer NumPy lernen möchte sollte diese Buch haben, aber nur als Einstieg sehen. Das Buch durchzuarbeiten ist absolut nicht nützlich. Durchlesen, um Eindrücke der Fähigkeiten der verschiedenen Mdoule zu erhalten, reicht vollkommen. Am besten lernen kann man dann Python bzw. NumPy/SciPy nur, wenn man an einem konkreten Problem lernt.

Erwähnt sei noch, dass die Vorschsläge des Autors an NumPy zu kommen etwas antiquiert sind, Ich empfehle einfach [...], da erhält man als Freeware Python mit allen noitwendigen Zusatzpaketen. Absolut perfekt zum direkt loslegen geeignet.

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NumPy Beginner's Guide - Second Edition 2nd Revised ed. Edition

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