Beginning Python Visualization: Crafting Visual Transformation Scripts (Books for Professionals by Professionals) [Paperback]

Shai Vaingast (Author)

Book Description

ISBN-10: 1430218436 | ISBN-13: 978-1430218432 | Publication Date: February 24, 2009 | Edition: 1

Data visualization is one of the sleeping giants of computer book publishing, and lies largely undiscovered except by people in the know, or computer science professors selling tens of thousands of copies on visualization. This book teaches data visualization without academic baggage to the people who actually need it and without theoretical baggage, namely IT personnel dealing with small and medium data sources, programmers faced with sudden visualization problems and engineers, economics, hobbyists interested in the environment and others.

Editorial Reviews

About the Author

Shai Vaingast has been an engineer, an engineering manager and a director of engineering since 1993. He has worked in the defense industry and in medical engineering, while being heavily involved with data visualization. He has a patent and also several patents pending.

Product Details

• Paperback: 384 pages
• Publisher: Apress; 1 edition (February 24, 2009)
• Language: English
• ISBN-10: 1430218436
• ISBN-13: 978-1430218432
• Product Dimensions: 9.2 x 7 x 1 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 3.9 out of 5 stars  See all reviews (18 customer reviews)
• Amazon Best Sellers Rank: #43,817 in Books (See Top 100 in Books)
  • #17 in Books > Computers & Technology > Computer Science > Software Engineering > Design Tools & Techniques
  • #20 in Books > Computers & Technology > Programming > Languages & Tools > Python
  • #24 in Books > Computers & Technology > Computer Science > Modeling & Simulation

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Customer Reviews

Most Helpful Customer Reviews

32 of 33 people found the following review helpful:

5.0 out of 5 stars An Excellent Book, May 9, 2009

By 

Ronald D. Stephens "Book Worm" (Newtown, CT United States) - See all my reviews
(REAL NAME)   

This review is from: Beginning Python Visualization: Crafting Visual Transformation Scripts (Books for Professionals by Professionals) (Paperback)

Sometimes a picture is worth a thousand words. "Beginning Python Visualization: Creating Visual Transformation Scripts", published in February 2009 by Apress, shows how Python and its related tools can be used to easily and effectively turn raw data into visual representations that communicate effectively. The author is Shai Vaingast, a professional engineer and engineering manager who needed to train scientists and engineers to do this kind of programming work. He was looking for a tutorial and reference work, and unable to find a suitable text, wound up writing his first book. He wrote in the easy and clear style of someone comfortable and engaged with the subject matter.

The book uses several very specific examples that illustrate general principles.

The first example is using GPS data. By using Python one can extract data from GPS receivers and enter it into the computer and manipulate it to do what one wants including creating graphs and charts. In this section he shows how to use CSV, comma separated values, as a most useful file format. He shows show to extract data from real world GPS devices and import it via serial ports and the PySerial module. It would be easy for the reader to duplicate and extend this project.

The heart of the book is coverage of useful examples utilizing MatPlotLib, NumPy and SciPy. These related tools are easy to use and fully integrated with Python. MatPlotLib is for plotting data and graphs, including interactive graphs and image files. NumPy is a powerful math library comparable to commercial tools like MatLab, and SciPy extends NumPy to for the sciences. Examples are numerous and include signal analysis using Fourier transforms.

There is also a section on Image Processing using PIL, the Python Imaging Library. This is used for relatively simple image cropping and sizing and also for bit by bit image processing. Interpolation and curve fitting are also well covered. For anyone wanting an introduction to graphical analysis of statistical data, this would be an excellent resource.

The author is obviously a professional in this field. He has a knack for good organizational style and a pragmatic approach to the work. In the book he says "Most of the time, research is organized chaos. The emphasis, however, should be on organized, not chaos." A real value I got from the book is a better understanding of data files, format, and organization as well as methods and guidelines for selecting file formats and storing and organizing data to enable fast and efficient data processing. It is obvious that this book was written by a practicing engineer.

The theme of the book is that Python can be an all purpose environment for data manipulation and visualization, using nothing but free and open source tools that are easily integrated and scriptable without using multiple programming languages. The book should be an invaluable tool for scientists and engineers but it is also easily accessible to anyone interested in math and data analysis. There is no need for an advanced math background. While, as a matter of full disclosure, I have undergraduate degrees in Math and Physics, I feel the book should be easily accessible to anyone with a solid high school math background who is seriously interested in the subject. The book contains a short introductory tutorial on the basics of Python so anyone familiar with programming in any language should be fine.

The book is an easy read from front to back, and I am sure it will also be a good reference resource for the future. The writing style is very clear and unforced and I found surprisingly few errors. While the Python world has a surplus of introductory and general books, books covering this kind of specific domain are especially welcome, and we could use more on other topics by competent authors.

At 363 pages the book is a surprisingly fast read. Its methodology is to use specific, short code examples to make all the key points. Most of the code samples are well selected, short and written in clear, concise Python. This is not the kind of book that overwhelms you with massive amounts of code. Either the book was well edited or else it was written by an exceptionally lucid thinker, or both.

So, if you want to learn how to process, organize, and visualize data from various sources using the Python language, I recommend this book to you.

I also have posted a podcast of an interview I did with the author at
www.awaretek.com/python/index.html

22 of 23 people found the following review helpful:

4.0 out of 5 stars Short on visualization - but great book nonetheless, March 19, 2009

By 

Bernard VdS - See all my reviews

This review is from: Beginning Python Visualization: Crafting Visual Transformation Scripts (Books for Professionals by Professionals) (Paperback)

After spending many years coding with a variety of languages/tools (C#/VB.Net,VBA, Matlab, various numerical libraries), I picked-up Python and am blown away with its versatility. Clean and minimal syntax, no bloated API, and an amazing array of open-source modules. Libraries such as Numpy,Scipy, Matplotlib, Pylab, Python(x,y) means I can ditch Matlab and keep all the functionality I need.

This book is a great introduction to Python for anyone who needs to handle and process data, and to the best open-source tools available to work with Python. It covers graphical display of data, but I wouldn't say it focuses on visualization per se.

This is one of five Python books I would recommend: the other four being the Python Essential Reference (Beazley), Rapid GUI Programming with Python and QT (Summerfield), Learning Python (Lutz), and Programming Collective Intelligence (Segaran).

Wish this had been around just a year ago!

18 of 20 people found the following review helpful:

4.0 out of 5 stars Excellent introduction to data processing and graphing in Python., March 7, 2009

By 

C. T. Brown - See all my reviews
(REAL NAME)   

This review is from: Beginning Python Visualization: Crafting Visual Transformation Scripts (Books for Professionals by Professionals) (Paperback)

I was the technical reviewer for this book, and I very much enjoyed the experience. The book is an excellent hands-on introduction to producing all sorts of useful graphs. It also discusses how to organize data files, write scripts properly, and do all sorts of things that scientists and presentation-oriented programmers will need to do sooner or later.

Technically, the book relies on scipy and matplotlib especially. These are very functional and well-known toolkits, so you won't be wasting your time on weird unsupported packages when reading this book.