This website contains links and other information accompanying Computational Frameworks for Political and Social Research with Python by Josh Cutler and Matt Dickenson. The book is part of Springer’s Textbooks on Political Analysis series. It will be published on May 30, 2020. You can pre-order the book from Springer or Amazon.

This book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.

Data for the exercises is available at dataverse.harvard.edu/dataverse/python-book.