A crash course in Python focusing on reading and visualizing data-sets used in Earth sciences.

Access materials via GitHub: https://ter.ps/noaapy

Day 1 will cover:

• Launching Jupyter Notebooks
• Working with arrays using the Numpy package
• Importing text datasets using the Pandas package
• Creating simple graphics with Matplotlib

Day 2 will cover:

• Importing scientific data formats, such as netCDF and GRIB2
• Creating maps from datasets
• Running python scripts

Installation requirements

"I am really new to Python!"

• I recommend launching binder, which is a "cloud version" of this course. No installation required!

"I have used Python before!"

• If you wish to run the examples locally, I recommend installing Anaconda. If you are having trouble with your installation, contact the instructor before the course or use binder.
• Download the contents of the GitHub repository to your computer.
• Launch Jupyter Notebooks from the Anaconda Navigator. This will open a window in your default browser. Navigate to the folder that contains the notebooks (*.ipynb) and click on the tutorial for the day.
• Additional packages:
  • Day 1: If you installed Anaconda, you will not need any additional packages
  • Day 2: Launch the Anaconda Prompt (Windows) or Terminal (MacOS/Linux). Then copy/paste and hit enter:

    conda install -c conda-forge cartopy
    conda install -c conda-forge netCDF4
    conda install -c conda-forge pygrib
    

  • If there are no errors, then you are set-up!
  • Alternatively, if you are familiar with environments, you can use the environments.yml to install the necessary packages.

I do not recommend:

• Using Python on a remote server for this tutorial (I cannot help troubleshoot)
• Using your operating system's Python or a shared Python installations unless you are advanced!

Pandas

• Short Introduction: https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html
• Cookbook for more details: https://pandas.pydata.org/pandas-docs/stable/user_guide/cookbook.html#cookbook

Matplotlib

• Pyplot Tutorial: https://matplotlib.org/3.1.1/tutorials/introductory/pyplot.html

Reading self describing file

• NETCDF
  • Detailed tutorial https://unidata.github.io/netcdf4-python/netCDF4/index.html.
• HDF files
  • The package h5py is similar to netcdf4.
  • User manual at http://docs.h5py.org/en/stable/.
• GRIB/GRIB2 files
  • World Meteorology Association standard format, e.g. commonly used with weather-related models like ECMWF and GFS.
  • Can be opened using pygrib.
  • Example usage at https://jswhit.github.io/pygrib/docs/.
• BUFR
  • Another common model format.
  • Open with python-bufr, part of the pytroll project.

Beginner Tutorials

• Youtube series for absolute beginners CS Dojo
• Research Software Engineering with Python Free eBook to enhance your workflow

Intermediate Tutorials

• Learn more about Python for Atmosphere and Ocean Scientists using Software Carpentry lesson plans.
• I have a longer workshop on Python for Earth Science with Rebekah
• Earth Observation using Python builds on the content of the workshop above.
• Python for Climate and Meteorology Another tutorial taught at AMS, a little more advanced.

Advanced tutorials Tutorials * May offer advanced workshop in spring