Python for Informatics: Exploring Information

About the Book
Author : Charles Severance
Publication Date : 2009
License : Creative Commons Attribution-Share Alike 3.0 Unported License 

Preface
The first 10 chapters are similar to the Think Python book but there have been some changes. Nearly all number-oriented exerciseshave been replaced with data-oriented exercises.Topics are presented in the order to needed to build increasingly sophisticated data analysis solutions. Some topics like try and catch are pulled forward and presented as part of the chapter on conditionals while other concepts like functions are left until they are needed to handle program complexity rather introduced as an early lesson in abstraction. The word “recursion” does not appear in the book at all. In chapters 11-14, nearly all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including automating tasks on your computer, retrieving data across the network, scraping web pages for data, using web services, parsing XML data, and creating and using databases using Structured Query Language.The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be applied even if one chooses not to become a professional programmer.
Book Contents
  • Why should you learn to write programs?
  • Variables, expressions and statements
  • Conditional execution
  • Functions
  • Iteration
  • Strings
  • Files
  • Lists
  • Dictionaries
  • Tuples
  • Regular expressions
  • Networked programs
  • Using Web Services
  • Using databases and Structured Query Language (SQL)
  • Automating common tasks on your computer
  • Python Programming on Windows
  • Python Programming on Macintosh
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