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Department of Linguistics and Oriental Languages


Ling 572 Syllabus

BDA 572-01 Syllabus (Wed)

BDA 572-02 Syllabus (Tues)

Optional Textbook Website

Tu Course outline

Wed Course outline

BDA Course outline

Online book draft

Text Analytics Certificate & Minor

Linguistics/BDA 572

Python for Social Scientists




Increasingly, social scientists find themselves facing exponentially larger data sets available on the internet and elsewhere without suitable tools to deal with them. Many social scientists end up using spreadsheet programs for their data-processing tasks and spend hours clicking around or copying and pasting, and then repeating the process for other data files. Not only is this a waste of time, but it often leaves you in a situation where it is hard to reproduce the steps that got you a particular result, making your work useless.

This course will show you how to use computing tools freely available via the scripting language Python to use your data more powerfully and effectively. The course touches on many topics of theoretical interest in the emerging field of data science, such as social networks and data visualization, but the focus is on manipulating data so that you can tailor it to the needs of your particular project. The course targets social science students and will assume no prior programming knowledge. Although many of the techniques are relevant to linguistics, economics, and geography, the course focuses on techniques that are applicable to a wide range of data sources, including images, social network data, web pages, blogs.

Tiopics covered include

  • Python Basics
  • Computing with arrays (Numpy)
  • Data analsyis with Data frame (Pandas)
  • Network analysis (Networkx)
  • Elements of text analytics (elementary text extraction, text classification)
  • Visualizing similarity relations


The course will use one optional text for introductory material (A Whirlwind tour of Python (Jake VenderPlas). and will also make heavy use of online course notes and freely available Python software. Links to notebooks keyed to both textbooks are provided in the course outline, which will be updated frequently through the course. Please refresh and visit frequently.


Tu Course outline

Wed Course outline

Prerequisites and Grading

No course pre-requisites. No knowledge of programming will be asssumed. Upper division standing. Some openness to acquiring computational skills. Some knowledge of what counts as interesting data in your own Social Science.

Grading will be based on assignments, an extended midterm assignment, and a final project.


Tu 1230-1345

Tu 1400-1515

Wed 1600-1840

Contact Info

Mailing address:
gawron at mail dot sdsu dot edu
Department of Linguistics and Oriental Languages
San Diego State University
5500 Campanile Drive
San Diego, CA 92182-7727
Telephone: (619) 594-0252
Office location: SHW, room 238

Unix | Computational Linguistics Lab