Computational methods for collecting, cleaning and analysing data are an increasingly important component of a social scientist’s toolkit. Central to engaging in these methods is the ability to write readable and effective code using a programming language.
The following topics are covered under this training series:
- Introduction to Python for social scientists - learn how to utilise the Python programming language for core social science research tasks.
- Collecting data I: web-scraping - learn how to collect data from websites using Python.
- Collecting data II: APIs - learn how to download data from online databases using Python and Application Programming Interfaces (APIs).
- Setting up your computational environment - learn how to create, manage and share a computational environment for social science research projects.
The training materials - including recordings, slides, and sample Python code - can be found in the following folders:
- code - run and/or download the code examples using our Jupyter notebook resources.
- installation - view instructions for how to download and install Python and other packages necessary for working with new forms of data.
- webinars - watch recordings of the coding demonstrations on our Youtube channel.
We are grateful to UKRI through the Economic and Social Research Council for their generous funding of this training series.
- To access learning materials from the wider New Forms of Data for Social Science Research training series: [Training Materials]
- To keep up to date with upcoming and past training events: [Events]
- To get in contact with feedback, ideas or to seek assistance: [Help]
Thank you and good luck on your journey exploring new forms of data!
Dr Julia Kasmire and Dr Diarmuid McDonnell
UK Data Service
University of Manchester