This was originally held on a ~weekly basis in the winter and spring of 2018, but the materials can be worked through at any pace.

We will update the repository as we have more sessions.

Contributors (alph. order):
Meg Fowler
Zack Labe
Baird Langenbrunner
Stephan Rasp
Chris Terai
Galen Yacalis

• Week 9 (Meg): 2018/08/28
  • Extreme value distributions in Python
• Week 10 (group discussion): 2018/09/04
  • Discussion on writing transparent/reproducible papers

• Week 1 (Baird and Stephan)
  • Install Python via Anaconda
  • Jupyter Notebook introduction
• Week 2 (Baird)
  • Python basics
  • numpy/scipy primer
  • pandas and csv/txt files
  • Opening MATLAB and NetCDF files
  • Simple plots with matplotlib
  • Simple maps with cartopy
• Week 3 (Chris)
  • Conda environments
  • Plotting and manipulating NetCDF data using UVCDAT
• Week 4 (Stephan)
  • xarray for gridded data sets
  • Debugging Python code
• Week 5 (Baird and Stephan)
  • matplotlib figures (intermediate level)
  • cartopy and plotting with maps
  • Animations in matplotlib
• Week 6 (Stephan)
  • Machine learning basics
  • keras neural network (applied to image classification: recognizing hand-written digits)
• Week 7 (Galen)
  • scikit-learn and advanced pandas
  • keras neural network (applied to volcanic eruption data set)
• Week 8 (Zack)
  • Data visualization tips (color maps, figure design)
  • Research workflow (documenting code and data)
  • See Zack's ClimatePython repository for more info!