Data visualization is one of the sleeping giants of computer book publishing. This book teaches data visualization without academic or theoretical baggage. It is a practical book aimed at IT personnel, programmers, engineers, economists and hobbyists.\nI was always 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 ana- sis, a field that I felt 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 gra- ing 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--for example, ways to ensure file names are unique and self-explanatory. With the increasing popularity of the Internet, I learned of GNU/Linux and the open source movement. I 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.