Beginning Python Visualization: Crafting Visual Transformation Scripts. 2nd edition

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Beginning Python Visualization: Crafting Visual Transformation Scripts. 2nd edition by Shai Vaingast

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I have always been drawn to math and computers, ever since I was a kid playing computer games on my Sinclair ZX81. When I attended university, I had a special interest in numerical analysis, a field that I feel combines math and computers ideally. During my career, I learned of MATLAB, widely popular for digital signal processing, numerical analysis, and feedback and control. MATLAB’s strong suits include a high-level programming language, excellent graphing capabilities, and numerous packages from almost every imaginable engineering field. But I found that MATLAB wasn’t enough. I worked with very large files and needed the ability to manipulate both text and data. So I combined Perl, AWK, and Bash scripts to write programs that automate data analysis and visualization. And along the way, I’ve developed practices and ideas involving the organization of data, such as ways to ensure file names are unique and self-explanatory.


With the increasing popularity of the Internet, I learned about GNU/Linux and the open source movement. I’ve made an effort to use open source software whenever possible, and so I’ve learned of GNU-Octave and gnuplot, which together provide excellent scientific computing functionality. That fit well on my Linux machine: Bash scripts, Perl and AWK, GNU-Octave, and gnuplot.


Knowing I was interested in programming languages and open source software, a friend suggested I give Python a try. My first impression was that it was just another programming language: I could do almost anything I needed with Perl and Bash, resorting to C/C++ if things got hairy. And I’d still need GNU-Octave and gnuplot, so what was the advantage? Eventually, I did learn Python and discovered that it is far better than my previous collection of tools. Python provides something that is extremely appealing: it’s a one-stop shop—you can do it all in Python.


I’ve shared my enthusiasm with friends and colleagues. Many who expressed interest with the ideas of data processing and visualization would ask, “Can you recommend a book that teaches the ideas you’re preaching?” And I would tell them, “Of course, numerous books cover this subject! But they didn’t want numerous books, just one, with information distilled to focus on data analysis and visualization. I realized there wasn’t such a title, and this was how the idea for this book originated.


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