title: Introduction to Scientific Computation and Programming in Python
author: Daniel T. Kaplan
description: This book provides students with the modern skills and concepts needed to be able to use a computer expressively in scientific work. The authors take an integrated approach by covering programming, important methods and techniques of scientific computation (graphics, the organization of data, data acquisition, numerical issues, etc.) and the organization of software. Balancing the best of the teach-a-package and teach-a-language approaches, the book teaches general-purpose language skills and concepts, and also takes advantage of existing package-like software so that realistic computations can be performed.
zlib_text: Undergraduate Topics in Computer Science
  Kent D. Lee
  Steve Hubbard
  Data 
  Structures and 
  Algorithms 
  with Python
  
  Undergraduate Topics in Computer
  Science
  
  Undergraduate Topics in Computer Science (UTiCS) delivers high-quality
  instructional content for undergraduates studying in all areas of computing and
  information science. From core foundational and theoretical material to ﬁnal-year
  topics and applications, UTiCS books take a fresh, concise, and modern approach
  and are ideal for self-study or for a one- or two-semester course. The texts are all
  authored by established experts in their ﬁelds, reviewed by an international advisory
  board, and contain numerous examples and problems. Many include fully worked
  solutions.
  More information about this series at http://www.springer.com/series/7592
  
  Kent D. Lee
  • Steve Hubbard
  Data Structures and
  Algorithms with Python
  123
  
  Kent D. Lee
  Steve Hubbard
  Luther College
  Decorah, IA
  USA
  ISSN 1863-7310
  ISSN 2197-1781
  (electronic)
  ISBN 978-3-319-13071-