Python & R course work for the UNIBE master in climate sciences. Each folder is one class.
In general the following packages are necessary, although some others may need to be imported. At a minimum, the following is required:
- seaborn (graphics)
- numpy
- pandas
- jupyter lab
- pip (to install specific modules as required)
__Check the rpy2 notebook for instructions on how to set up rpy2 - used sporadically to translate R into Python.
- rpy2 (to be installed with pip not conda)
The Aquacrop OSPY package is used to run a randomization experiment on irrigation dates within a simple crop model framework.
Follow the instructions in the README.md file in the climate-agriculture folder to properly install the packages in the recomended order.
The R script used to generate the examples in the slides is reinterpreted using a mix of Python and the rpy2 packages.
Pandas and seaborn is used to accomplish the weather and climate data module.
R, Python, pyr2 used to accomplish the assignments and follow along with the coding in the course. Sphinx is developped to generate the .pdf homework files in a manner equivalent to latex.
Weekly solutions provided in R and in Python / rpy2 (depending on time!)
Other random stuff that comes up / empty for the moment
Kept in a separate repo.
Data files are generally not included in this repository, contact me if you need.