During the past years the use of of Python and other tools originally created for more traditional type of software programming has become very popular in the area of data driven science. The scientific Python ecosystem has become mature quite fast during the past years. Using open source tools makes your work more accessible to others. This is an important advantage especially in academia and motivates many to the transition from commercial software like Matlab, Maple or Mathematica to Python and the libraries available.
We will try to answer questions, which might be interesting for scientists working with data. With a focus on practical tasks, we want study how to write good, efficient code and which tools to use to organize our data and the code. If helpful for understanding the big picture, we will discuss a bit of theory.
Prerequisites:
- basic understanding of (scripted) programing languages (loops, variables, functions, classes, ...)
- knowledge of basic Python syntax (e.g. implement easy functions, importing modules, ...)
- basic GIT knowledge
- use of a command line
- Organizing code and data: Advanced Git, Github and more
- 2019-04-01 9:30 - 12:30 Seminarraum Simony-Haus EG07 (SIMH-EG/07)
- How to make code beautiful: Python beyond basics
- 2019-04-03 9:30 - 12:30 GUTH-SR 03 (GUTH-EG/17)
- The Python Scientific Ecosystem
- 2019-04-04 9:30 - 12:30 GUTH-SR 02 (GUTH-EG/14)
- GIS & Python
- 2019-04-15 9:30 - 12:30 GUTH-SR 02 (GUTH-EG/14)