10  Your project

The third part of this course is a small data analysis project that you carry out in groups of 2. The goal is to apply the skills from chapters 02–09 to a topic of your choice. Use git and either GitHub or the university GitLab to share code within your group (see Section 11.8 for an introduction). The repository should be public (or shared with the instructor) so that the instructors can follow your progress. Here is the timeline:

  1. Find a project. Choose a dataset and a question you want to answer. The dataset can come from any source — public APIs (e.g. World Bank, Eurostat, OpenStreetMap), CSV files from the web, or data you collect yourself. The question should be concrete enough that you can answer it with several plots, tables, and statistical tests.

  2. Hand in your project idea (by Pentecost – Pfingsten – break). Write a short description (one to two pages are enough) containing:

    • What data will you use, and where does it come from?
    • What question(s) do you want to answer?

  3. Implement and present your project (last two or three sessions). Build a Jupyter notebook that loads, cleans, analyzes, and visualizes your data. Each project will be presented briefly in class. Your presentation should cover:

    • The question and the data source.
    • The main steps of your analysis.
    • Your results (plots, tables, statistical findings).
    • Any difficulties you encountered and how you solved them.