In recent years, Python has established itself alongside R at the forefront of numerical programming languages. Very similar to the programming with MATLAB, mathematical-statistical representations from technical literature, such as econometric textbooks, can be implemented compactly and easily in the programming language Python and its scientific extensions. Following a concise introduction to the general-purpose language framework, the students learn how to design, implement and exchange their own data analysis projects in an object-oriented way:
- Introduction to Python and object orientation.
- Numerical programming – compared to MATLAB and R.
- Data formats, handling, exports and imports – file and web.
- Visual illustrations and presentation of scientific results.
- Statistical analysis with further applications in economics.
The participants get familiar with Python’s way of thinking and learn how to solve (scientific) programming problems with a state-of-the-art tool.