Welcome to the official course website for the Introduction to Python for Social Science optional methods module at the Department of Politics and International Relations, University of Oxford.

I will be posting all slides, workbooks, practice sets and solutions on this website. Recorded lectures will be hosted on Canvas/Panopto. Information regarding office hours will be sent out in the coming days.

Course Details

Lectures will be held weekly at time/place tbd. Office hours will be discussed in the first lectures.

You can find an older syllabus for the course here.

Lecture Slides

I’m using reveal.js for the lecture slides, so they should be viewable in the browser on any device. pdf (beamer) format slides are also available lower down the page.

You might note that the previous year’s slides are still accessible via the linked GitHub. Please note that there are some substantial changes being made to the course, and the slides in the GitHub may not reflect this yet.

Materials

Week	`reveal.js`	Code Examples	Code Exercises	Code Solutions	Data
1	slides	examples	exercises	solutions	None
2	slides	examples	exercises	solutions	BES
3	slides	examples	exercises	solutions	None
4	slides	examples	exercises	solutions	None
5	slides	examples	exercises	solutions	None
6	slides	examples	exercises	solutions	None
7	slides	examples	exercises	solutions	None
8	slides	Twitter API Selenium	None	None	None

About Me

My name is Musashi Harukawa, I am a DPhil Politics student at the University of Oxford. Prior to returning to academia, I worked as a quantitative analyst/data scientist at a stock exchange in Tokyo and an English teacher in Moscow.

I research computational methods for unstructured (i.e. text or image) data and digital political campaigning. I also have a blog!

Some presentations etc.

“Estimating the Micro_Targeting Effect: Evidence from a Survey Experiment During the 2020 U.S. Presidential Election”, Under Review, Link to Presentation

“Comparative Government Revision Class”