Abstract

Other than with R, getting started with Python can be burdensome at times as there is no one-stop shop solution like RStudio. Although tons of introductory tutorials for Python are available on the web, navigating and setting up one’s programming environment can be challenging, especially for users with little programming experience. To lower the burden of getting started with Python, we will talk in this workshop about the basics of Python, installing and maintaining virtual environments and the various graphical user interfaces and integrated development environments out there like Jupyter Notebooks, Google Colab, and Anaconda. We show situations where Python may be beneficial for your research and when you may choose to go with R. Please note that this talk is the first part of a two-day workshop in the Social Science Data Lab. In the second event (February 22, 2023), we will focus our attention on implementing a simple machine learning routine in Python.

Presenters

Ruben Bach is a postdoctoral researcher at the MZES, University of Mannheim, focusing on social science quantitative research methods. His interests include topics related to big data in the social sciences, machine learning, causal inference, and survey research.

Andreas Küpfer is a doctoral researcher at the University of Darmstadt. His interdisciplinary research interests include text as data, applying machine learning technologies, and substantial inference in the fields of political communication and political competition.