Computing for the Social Sciences and Humanities, Spring 2013

Workshop Goals and Topics

This is an non-credit applied workshop focusing on a pragmatic understanding of programming languages and software libraries, specifically oriented towards students in the social sciences and humanities with emerging research projects requiring basic programming skills.

The workshop's goals include unshackling academic researchers from the constraints of commercial, general-purpose statistics/GIS software and to free them from the limitations of working with pre-existing and pre-formatted data sets. Students in the workshop will learn to write programs in the interpreted programming language Python and the (open-source) statistical software language/environment R, as well as learning to use databases and to interact with a wide variety of existing software. The simultaneous instruction of two very different principal programming languages is intentional: the workshop's secondary goals are to demonstrate that data can be created, analyzed and visualized by a diversity of methods, and to encourage students not to be intimidated by unfamiliar computer programming dialects and interfaces. The workshop will introduce methods required to parse text files, scrape data from other sources, write structured programs for statistical analysis, create and query databases, visualize datasets, and conduct network analysis.

Assignments and Help Sessions

Each weekly meeting will be accompanied by an openly collaborative, take-home programming assignment which will be due before the following class. After each class, a help session and tutoring hours will be provided for those requiring extra guidance on the assignment. The programming assignments will often be cumulative and build on one another, so completing the functionality of each assignment is crucial.

Spring Schedule

Week 1 (4/4/2013)	Operating Systems and Computer Science Basics
	Introduction to basic concepts of operating systems and programming languages. Introduction to interpreted programming languages Python and R, with comparison to SPSS/Stata. Introduction to command-line interfaces. Assignment 1 is available here
Week 2 (4/11/2013)	Data types and data structures
	Lists, arrays, dictionaries. Vectors and matrices. Operations on these data types in Python and R. Introduction to the `scipy` data structure library for Python. Readings to be done before Week 2 meeting: Learning Python, Ch 4: "Introducing Python Object Types", Ch. 5: "Numeric Types" , and Ch. 7: "Strings". R in a Nutshell, Ch. 3 "A Short R Tutorial". Learning Python, Ch. 8: "Lists and Dictionaries".
Week 3 (4/18/2013)	Structured programming and code management
	Conditional statements, loops, functions, modules. Using a text editor and organizing code in separate files. Introduction to programming styles—functional, imperative, object-oriented. Assignment 2
Week 4 (Friday, 4/26/2013)	Input and Output NOTE: changed meeting date
	Storing analyzed data for later reuse (Python's `pickle` and `cPickle` module).
Week 5 (5/2/2013 in Searle 240B)	Web scraping and Content analysis NOTE: changed location

Week 6 (5/9/2013)	Plotting, Graphing, Visualization
	Visualizing descriptive statistics in R (histograms, box plots, scatter plots, etc.) Introduction to `matplotlib` for Python.
Week 7 (5/16/2013)	Data management and Databases
	Introduction to relational databases, which provide stable and network-accessible storage of medium-to-large (but not very large) datasets. Comparison of spreadsheet interfaces (Excel, SPSS) with relational databases like MySQL. Introduction to `MySQLdb` library for Python. SQL books available on Proquest Beaulieu, Alan. Learning SQL, Second Edition, 2009. There's also a copy of this in SS402 if you want to check it out in person. Kline, Kevin. SQL in a Nutshell, 2008. This is mostly just a command reference, which can be useful when you want to understand the many parameters to e.g., `ALTER TABLE`. The book tries to distinguish between variant syntax for Microsoft SQL (which we hope you won't ever have to use) and MySQL. Molinaro, Anthony. SQL Cookbook, 2005. This book ranges from simple questions "How do I insert a new row" to the more complex, and is a good companion to a tutorial like Learning SQL.
Week 8 (5/23/2013)	Data Analysis & Data Mining
	Building structured, multi-stage programs that systematically evaluate hypotheses and explore patterns in data.
Week 9 (5/30/2013)	Network Analysis
	Basics of network representation, manipulation and visualization in Python's `networkx` library and R's `sna, network, igraph.`
Week 10 (6/6/2013)	TBA

Software

Python: we will be using the Enthought distribution. Please download and install the appropriate version for your operating system and let us know if you have any problems.
R: available for download here.
Cygwin: for those running Windows, please install this POSIX-like command-line environment. (See instructions for installing Cygwin)
Text editors: you should find a scripting editor you enjoy using. Our top two picks for beginners are TextWrangler (for OS X) and Notepad++ (for Windows).

Readings

Selected readings will be assigned from the following texts (some available in their entirety online):

Adler, Joseph (2012). R in a Nutshell. NEW 2nd edition for 2013! Much more than a big index of functions, this is a true language tutorial with practical examples and pulls no punches with the low-level explications. Recommended!
Teetor, Paul (2012). R Cookbook. NEW for 2013! Taking a simpler, more straightforward approach than R in a Nutshell, this book includes a lot of examples of basic R techniques. Written by one of the organizers of the Chicago R User Group (see below)!
Lutz, Mark (2009). Learning Python, 4th Edition. A little bloated, but as good an introduction to the language as any, without requiring a computer science background. You'll want to ignore the material on Python 3.x for now.
Silberschatz, Galvin and Gagne (2008). Operating System Concepts, 8th Edition. Relatively lucid, up-to-date OS textbook. Absolutely crucial information to becoming a good programmer that is rarely taught in introductory courses. Available at Eckhart library.

Additional Texts

Albing, Carl et. al. (2007). bash cookbook. A good way to learn about all the different convenient things you can do by mastering a UNIX shell.
Peek et. al. (2002). Unix Power Tools, Third Edition. By now a little dated, but every respectable command-line user has once had this book in their bathroom.
Friedl, Jeffrey E.F. (2006). Mastering Regular Expressions, Third Edition. You'll probably want to stick to Chapter 1 here, but this is a good introduction to the vast world of regular expressions.

Lecture Slides

Local Meetups

UPDATED for 2013!

One easy, ethnographically-oriented way to help adapt to contemporary computing culture is to crash one of Chicago's many friendly user groups and meetups, which typically offer free pizza, beer, and PowerPoint presentations in various downtown office spaces and taverns.

Open Gov Hack Night is an unparalleled mashup of civic-minded developers, municipal and regional stakeholders, journalists, and moonlighting grad students. Meets at 1871, a tech startup co-working center on the 12th floor of the Merchandise Mart. (Note: Open Gov Hack Night sometimes held concurrently with the socially-motivated DataPotluck)
ChiPy is Chicago's Python user group, where every meeting is "the best meeting ever", and which has recently been held at the offices of Threadless, The Onion, and Groupon.
Chicago R User Group: let off steam from another long day of hacking financial time series data here.

¹ Students will be required to install Python and R distributions on their own computers.