Python for Informatics Exploring Data Charles Severance 3 AUDIOBOOK COLLECTIONS 6 BOOK COLLECTIONS Python for Informatics Exploring Information Version 0 0 3 Charles Severance Copyright 2009 2010 Charles Severance Printing history December 2009 Begin to produce Python for Informatics Exploring Information by re mixing Think Python How to Think Like a Computer Scientist June 2008 Major revision changed title to Think Python How to Think Like a Computer Scientist August 2007 Major revision changed title to How to Think Like a Python Programmer April 2002 First edition of How to Think Like a Computer Scientist This work is licensed under a Creative Commons Attribution Share Alike 3 0 Unported License This license is available at creativecommons org licenses by sa 3 0 The original form of this book is LATEX source code Compiling this LATEX source has the effect of generating a device independent representation of a textbook which can be converted to other formats and printed The LATEX source for the Think Python How to Think Like a Computer Scientist version of this book is available from http www thinkpython com The LATEX source for the Python for Informatics Exploring Information version of the book is available for the moment from http source sakaiproject org contrib csev trunk pyinf The cover images were provided by Dr Lada Adamic and are used with permission Preface Python for Informatics Remixing an Open Book It is quite natural for academics who are continuously told to publish or perish to want to always create something from scratch that is their own fresh creation This book is an experiment in not starting from scratch but instead re mixing the book titled Think Python How to Think Like a Computer Scientist written by Allen B Downey Jeff Elkner and others In December of 2009 I was preparing to teach SI502 Networked Programming at the University of Michigan for the fth semester in a row and decided it was time to write a Python textbook that focused on exploring data instead of understanding algorithms and ab stractions My goal in SI502 is to teach people life long data handling skills using Python Few of my students were planning to be be professional computer programmers Instead they planned be librarians managers lawyers biologists economists etc who happened to want to skillfully use technology in their chosen eld I never seemed to nd the perfect data oriented Python book for my course so I set out to write just such a book Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break Dr Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester It is a well written Computer Science text with a focus on short direct explanations and ease of learning As the copyright holder of Think Python Allen has given me permission to change the book s license from the GNU Free Documentation License to the more recent Creative Commons Attribution Share Alike license This follows a general shift in open doc umentation licenses moving from the GFDL to the CC BY SA i e Wikipedia Using the CC BY SA license maintains the book s strong copyleft tradition while making it even more straightforward for new authors to reuse this material as they see t I expect that by the time I am done with Python for Informatics over fty percent of the book will be new The overall structure will be changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis Then I will add chapters on regular expressions data visualization working with spreadsheet data structured query language using SQLite web scraping and calling REST based Application Program Interfaces vi Chapter 0 Preface The ultimate goal in the shift from a Computer Science to an Informatics focus is to pull topics into the rst programming class that can be applied even if one chooses not to be come a professional programmer What is interesting even with this change of focus is how much of the original Think Python book material is directly relevant to this book and how much will t right into Python for Informatics with virtually no change By starting with the Think Python book I don t have to write the basic descriptions of the Python language or how to debug programs and instead focus on the topical material that is the value add of Python for Informatics Students who nd this book interesting and want to further explore a career as a profes sional programmer should probably look at the Think Python book Because there is a lot of overlap between the two books you will quickly pick up skills in the additional areas of Computer Science which are covered in Think Python And given that the books have a similar writing style and at times have identical text and examples you should be able to pick up these new topics with a minimum of effort I hope that this book serves an example of why open materials are so important to the future of education and want to thank Allen B Downey and Cambridge University Press for their forward looking decision to make the book available under an open Copyright I hope they are pleased with the results of my efforts and I hope that you the reader are pleased with our collective efforts Charles Severance www dr chuck com December 19 2009 Charles Severance is a Clinical Assistant Professor at the University of Michigan School of Information Draft Version Instructions The copy of this book you are looking at is currently a draft and still in development The general roadmap for the rest of the development book is as follows Teach SI502 Networked Programming at University of Michigan Winter 2010 The rst 10 chapters of the book will be used for the rst four weeks of the course At least three more chapters will be written for SI502 and distributed during the semester that line up with the topics in the second half of SI502 Networked Programming Databases and Using Web Services There are four more chapters planned at some point Advanced Functions Regu lar Expressions Automating Common Tasks and Visualizing data These are not currently in the scope of SI502 for Winter 2010 Like all books being written and used in a course at the same time student feedback is essential to producing a strong book So I hope that students will look at the book and help me nd simple errors places where ideas jump too fast improvements in the glossary debugging and exercises in