NumPy Beginner's Guide: An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library. , Second Edition

I had written a review for this book on my blog here: http://nipunbatra.wordpress.com/2013/06/11/book-review-numpy-beginners-guide-second-edition/ I would recommend this book highly. It is very good for newcomers. For Python oldies it might be a little slow. NumPy Beginner's Guide - Second Edition

The book is very well written, and tries (quite successfully) to address this specialized, complicated subject in a light, simplified manner without losing depth and oversimplifying. The book includes many down to earth examples and sample code, and many interesting exercises that help implement the material.It starts with a nice, gradual introduction to NumPy, its functions, data structures and uses (and of course, how to install it). Then, the book addresses how to handle, analyze and manipulate larger datasets with examples from stock market data. Around half way, the book focuses on matrices and linear systems. The last few subjects cover advanced topics which I didn't delve into yet.All in all, a very good book, fun to read and useful. Recommended to anyone interested in manipulating arrays, matrices and large datasets in python efficiently.For further information, please see the mini-review on my blog:http://bioblog3d.wordpress.com/2013/06/15/numpy-beginners-guide-review/

Who is it for:This is an excellent book for the Python programmer who wants to extend their knowledge into mathematical programming and those with a mathematical or engineering background who want to leverage open source alternatives to commercial tools by using the NumPy with Python.Installation and other packages:Installation on the main platforms and the relationship between NumPy and SciPy, and using the library with Matplotlib and other Python modules is well covered.What's covered:The coverage is goes from creating vectors and multi-dimensional matrices through calculating Eigenvectors, the FFT, complex numbers, polynomial fitting and many others.Example Code:The examples I've followed are well thought through and illustrate the use the relevant parts of the NumPy API required in a clear and concise manner. An increasing amount of mathematical background is needed and for a beginner the book should be read in conjunction with a text book covering the relevant material.Recommendation:I would heartily recommend the book both as tool for learning and as a working reference for the NumPy library and wish it had been available when I was going up the learning curve.

I wish to comment on the excellent book by Ivan Idris. The text entitled NumPy Beginner's Guide, Second Edition is an outstanding book for a broad range of computer enthusiasts. While not all computer nerds are necessarily interested in Programming per se', in light of the growth and momentum of digital media, it is now a fact of life that many fields of employment require some basic introduction to computer programming. Whether you are a business or financial analyst, or perhaps a serious computer wanabee, or even a College student, it is now time to take the first step. With the momentum seen in the computer language of Python, many people who would otherwise not be inclined to learn this skill, never the less are posing some interest and saying "I wonder if I could do that?" This book will show you how. Since this book covers programming with Python from A to Z, and provides an easy path of self-learning, a number of people with a broad range of computer and math skills can accomplish these tasks.Yes, sitting in the classroom somewhere and listening to someone lecture on the fine points of computer programming may be the road to success for lots of people, but it is not beyond achieving this same goal of learning new skills by self-study ... In the first few pages of this book, the notion of interactive python is introduced (called IPython). That is, one would take a canned script or snippet of sample code and run it in a command line interpreter or interactive shell. That is a fancy name for entering code at a prompt, essentially using a cut and paste routine. How simple can it be ... Since the subject text has a bazillion examples or python routines and coding structure, one can view a broad range of examples from the simplistic to the quite advanced level. With this book, following along step by step or page by page, you can almost become a computer (read python) programmer, overnight. I. E., one enters the example code, then follows the book and reviews the resulting output, along with subtle hints about the interpreter operation. The shell (or debugger) will allow you to step into the code line by line and view the resultant computer operations. Thus, not only do you have visual feedback (to check your work) but one of the books highlights are the numerous "On-line resources and help" that will provide you with support material at a click of a mouse. As an aside, I regularly read the Yahoo email Group entitled "the Python Community"([...] each day where someone asks the basic question about "Where can I learn Python by way of self-study?" This book provides that answer and opportunity. So Chapter 1 of this book is appropriately entitled"NumPy Quick Start". As you begin Chapter 2, you will soon recognize the format that follows, and gives the reader (or student) an introduction to key Python topics. For example, to program a machine to organize and otherwise manipulate data, be it text or a set of integers, we need to know some basic objects such as data structures. So after a few words about a data structure like an "array", one needs to create an array using examples (code) from the book. With further comments about "What happened?", while creating an array, you will be provided a mini quiz or "Pop quiz" that will test your comprehension and understanding of the concept at hand. Obviously, the quiz is a good reinforcement tool to aid learning. Next, the author uses additional examples to lead you through some more variations of the objects that you are studying. That is: the "Time for Action" is now an opportunity to alter or create alternate arrays by manipulating their dimensions etc. This Time for Action is actually a number of requests (or examples) for "you to try it". Now, not only are you learning new skills and techniques but in fact are "gaining experience" with Python. As a computer wanabee, I now recommend that you take a pencil in hand and copy some of the examples on paper (that you may be interested in). This may be seen as a proactive learning experience and will help you understand some rudimentary things like the syntax (the ways words combine to form phrases or code) of the Python language.Let me clarify a point here, about this text. It is true that this text is focused on mathematical techniques that the average beginner may not be quite ready for, I. E. basic Statistics and Linear Models as seen in Chapter 3, but I would argue that as we discussed above, the layout of the book and its associated (read: excellent) format allows one to learn and gain experience, one step at a time. Chapter 4 of the book lays out additional functions that start to exhibit the power of NumPy. For example (page 95) starts a discussion of Polynomials, in layman's terms, that of finding a function the fits a set of data. I am of course assuming that you have some interest in math and "numbers" per se', if in fact you have searched for this book at Amazon.com Other Chapters go on to highlight such programming techniques as related to:(3). CSV files, Simple Statistics, Linear Models and Trend Lines, (4). Convenient Functions,(5). Matrices and Universal Functions, (6) Linear Algebra, Random Numbers, Distributions,(7). Special Routines for Sorting, Searching, Financial Functions. (8) Quality and Testing [of software],(9). Plotting (results such as Graphs, Histograms, Scatter Plots etc.),(10.) SciPy., a Python based system for Scientists, Engineering and Mathematics. and(11). PyGames. What could be more fun than learning to program games in Python. As you inspect this book, you will find something of interest to everyone who is acquainted with the word Python.It is an excellent book in a format that is easy to find a keyword or idea and will remain a valuable resource to you, for a long time.

I have been reviewing Ivan Idris Numpy `beginner's guide', second edition of a great book. While in the first edition he started explaining iPython and Matplotlib, this second is an even more practical guide: "less theory, more results". The first chapter deals with essentials as Python, iPython and libraries as NumPy, Matplotlib and Scipy and ends with applications to vectors and arrays using those tools. Just then in second chapter he goes deep into NumPy fundamentals with many exercises using arrays, including passing from an array to a list (exercise that helps to understand what are the differences and advantages of each data type.)Chapter 3 relates to common functions and applications to, example, finances and times. Chapter 4 deals with how to fit polynomials and also Smoothing and as an example, the Hanning function. Chapter 5 is related to matrices and "ufuncs" (short by universal functions) including how to create it and use with a code. These ideas are applied to a classic, Fibonacci numbers but also to Lissajous curves and the drawing of sawtooth and triangle waves, and also how to work with bitwise comparison operations. Up to this point this is the perfect companion for a crash course on the uses of Python and libraries like NumPy; however is also strong enough to be used as part of a college lecture or as the tool that should not be absent in your tool box and desk. Is hard to summarize further chapters; is a very good book because Idris shows his ability to explain in clear and concise sentences and then he applies immediately to exercises in a variety of areas. If you can't find what you need in this book, the only solution might be a do it yourself solution, based in the' big book', the web! In chapter 6 he explains applications to Linear Algebra including eigenvalues and eigenvectors, Fourier Transform, random numbers and applications to a gambling show. In chapter 7 he works with complex numbers, including sorting and searching, and even plays with Bessel functions. Chapter 8 deals on Assuring Quality with Testing and how to assert and compare arrays. Chapter 9 is one of my favorites, because Idris shows excellent examples on how to plot using Matplotlib, including animations! If you cannot impress your audience with these tools, likely they are dead. In Chapter 10 he goes deeper on libraries like Scipy (NumPy + SciPy are essentials on dealing with big arrays of data, like images) but this time Idris also give us hints in how to deal with audio processing. Finally in Chapter 11, he talks about PyGame along with Matplotlib, Numpy and applications to ... Artificial Intelligence, and simulations of life.Certainly one book can hardly cover ALL `what we need'. However, is up to us to get the most of a tool. If you work on Engineering or Science and are in need to deal with data, vectors, matrices, arrays, sounds or images, if you need to plot and to make things evident to others, if you need a data handling Swiss tool in your toolkit, this is it, clear, concise, full of many examples in so many areas that you will always have something to talk with others even from areas different to yours. Read it, use it, enjoy it.