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eBook SciPy and NumPy: An Overview for Developers epub

by Eli Bressert

eBook SciPy and NumPy: An Overview for Developers epub
  • ISBN: 1449305466
  • Author: Eli Bressert
  • Genre: Techno
  • Subcategory: Programming Languages
  • Language: English
  • Publisher: O'Reilly Media; 1 edition (November 25, 2012)
  • Pages: 57 pages
  • ePUB size: 1494 kb
  • FB2 size 1330 kb
  • Formats doc txt lit lrf

Eli Bressert was born in Tucson, Arizona. He worked as a science imager for NASA's Chandra X-ray Space Telescope optimizing science images which are frequently seen on book covers, newspapers, television, and other media

Eli Bressert was born in Tucson, Arizona. He worked as a science imager for NASA's Chandra X-ray Space Telescope optimizing science images which are frequently seen on book covers, newspapers, television, and other media. Afterward, Eli obtained his PhD in astrophysics at the University of Exeter and is currently a Bolton Fellow at CSIRO Astronomy and Space Science in Sydney, Australia. For the past six years Eli has been programming in Python and giving Python lectures at Harvard University, the European Space Astronomy Centre, and the European Southern Observatory.

Eli Bressert was born in Tucson, Arizona.

Printed in the United States of America. Published by O’Reilly Media, In. 1005 Gravenstein Highway North, Sebastopol, CA 95472. Safari Books Online offers a range of product mixes and pricing programs for organizations, government agencies, and individuals.

Published by O’Reilly Media. Beijing ⋅ Cambridge ⋅ Farnham ⋅ Köln ⋅ Sebastopol ⋅ Tokyo. Among the best of these are SciPy and NumPy

Published by O’Reilly Media. Among the best of these are SciPy and NumPy. NumPy and SciPy are the bread-and-butter Python extensions for numerical arrays and advanced data analysis. Hence, knowing what tools they contain and how to use them will make any programmer’s life more enjoyable. This book will cover their uses, ranging from simple array creation to machine learning.

SciPy and NumPy book. Goodreads helps you keep track of books you want to read. Start by marking SciPy and NumPy: An Overview for Developers as Want to Read: Want to Read savin. ant to Read.

SciPy and NumPy Eli Bressert Beijing, Cambridge, Farnham Kăoln Sebastopol Tokyo 9781449305468 text.

A Programmer's Guide to Data Mining by Ron Zacharski Online.

SciPy and NumPy : An Overview for Developers Eli Bressert is a PhD astrophysics student, Chandra Science Imager, and .

SciPy and NumPy : An Overview for Developers. By (author) Eli Bressert. Eli Bressert is a PhD astrophysics student, Chandra Science Imager, and contributor to astrobetter. He develops Python apps like ATpy, APLpy, and Luj. show more. Close X. Learn about new offers and get more deals by joining our newsletter.

Eli Bressert (2012). SciPy and NumPy: an overview for developers. p. 43. ^ Birodkar, Vighnesh (2014). GSOC 2014 – Signing Off".

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You’ll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries.

Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You’ll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level.

The new edition is now available, fully revised and updated in June 2013.

Learn the capabilities of NumPy arrays, element-by-element operations, and core mathematical operationsSolve minimization problems quickly with SciPy’s optimization packageUse SciPy functions for interpolation, from simple univariate to complex multivariate casesApply a variety of SciPy statistical tools such as distributions and functionsLearn SciPy’s spatial and cluster analysis classesSave operation time and memory usage with sparse matrices
Comments: (7)
There are a number of *free* webpages, tutorials and PDF's that explain numpy and scipy, at least one of them is longer than this 'book.' I am reviewing this booklet in light of those resources. It fails on two accounts:

As another reviewer has pointed out there are a number or errors in the examples (I suspect these are typos but for such a short booklet with so few examples there is no excuse for so many typos). Note, that I am not so picky about grammar errors - but lines of code are intended to be typed in verbatim. How frustrating it is to have error filled examples. [This is less excusable than grammar errors because bad code can be found so easily by actually trying it]

Further, this booklet doesn't have enough detail on these libraries to explain how and when one would want to use some of these algorithms and it is too long to be a cheat sheet for calling sequences (and outrageously priced for a mere cheat sheet). It is neither fish nor fowl so I do not recommend wasting your time or money on it. An internet search will turn up many explanations of both scipy and numpy you can find the details *and* cheat sheets for free.
First off, this short monograph is intended to give someone who is a newly intermediate python user the working knowledge of numpy and scipy modules. This is not intended to explore every aspect in detail. Python and its modules, in general, are "living" objects, thus things change making internet documentation the best choice for an in depth look at the inner workings. Ideally this is for someone who has worked with matlab, mathematica,etc and needs similar functionality in a python environment. One of the reviewers stated syntaxial errors, but I haven't noticed any yet. I do think the author left out another import module which is also used frequently along with numpy and scipy, matplotlib used for 2D plotting. However there are two good workbooks for beginners in both numpy and matplotlib:

NumPy 1.5 Beginner's Guide
Matplotlib for Python Developers.

I do think the price point for this text is too high, should be more around $10-12.
As with a lot of the other reviewers, I was disappointed that this book is really just a short pamphlet, giving a sampling of what SciPy and NumPy can do. I had been on the waiting list for this for many months, and I think when I advanced purchased it it was going to be much more ambitious and longer. There was a long delay in getting this out and things may have changed, I don't know. In any case the book isn't bad, it's just misleading the buyer into thinking they are getting a real book when it isn't. Definitely not worth the $18 I paid for it, I think it would be better priced at $10 or so, and for the description to highlight the form factor of the book.
I have not completed the book yet. But as other reviewers mentioned, this book is surprisingly (shockingly) short. NumPy coverage is very minimal.

In general I am OK with the way concepts are introduced, and it is clear that the author has considerable experience in scientific programming, in Python. But coverage is simply insufficient, in my opinion.

There are also, couple of syntax errors. They are not critical, you can correct them easily, but after feeling kind of disappointed with the content, it just adds .. to the injury.
This book is simply a man (manual) page. Lacks a lot of examples. I have online resources worth spending much time on than this book. However, if you want to carry it in your pocket to be present all the times, its worth a buy. Choice is yours.
I use scipy and numpy on a daily basis and was hoping to find some tricks that I didn't know about.
It is pretty standard stuff found easily on the internet from a quick search.
Thin paperback for the money. mostly NumPi with little SciPi
I am very happy with my purchse and I will order from this vendor again.
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