computer scientists. The reader’s main line of work is research or R&D, in his or her field of
interest, be it astrophysics, signal and image processing, or biology. The audience includes
The book can be appealing to these groups for different reasons. For scientists and engi-
neers, the book provides the means to be more productive in their work, without investing a
considerable amount of time learning new tools and programs that constantly change. For
programmers and computer enthusiasts, the book can serve as an appetizer, opening up their
world to Python. And because of the unique approach presented here, they might share the
enthusiasm the author has for this wonderful software world. Perhaps it will even entice them
to be part of the large and growing open source community, sharing their own code.
It is assumed that the reader does have minimal proficiency with a computer; namely he
or she must know how to manipulate files, install applications, view and edit files, and use
applications to generate reports and presentations. Background in numerical analysis, signal
processing, and image processing, as well as programming, is of help, but not required.
This book does not intend to serve as an encyclopedia of programming in Python and the
covered packages; nor does it try to be complete. It serves as an introduction to data analysis
and visualization in Python and covers most of the topics associated with that field.