Valparaiso University in Valparaiso, Indiana will be hosting a Unidata Regional Software Training Workshop March 14-15, 2019. Unidata software developers will be leading the two-day Python-focused workshop, which will cover the use of the MetPy and Siphon packages in the context of atmospheric science. A basic familiarity with Python is assumed — check out the Unidata Online Python Training for a refresher.
Unidata holds regional workshops in part to facilitate easy access to software training for those who may not be able to travel to training workshops held at the Unidata Program Center in Boulder, Colorado. Attendance is explicitly not limited to Valparaiso students and staff; we encourage those within easy travel distance to consider attending.
MetPy / Siphon Topics
- Getting Python packages w/Conda
- Jupyter notebook introduction
- Introduction to Numpy
- Introduction to Xarray
- Introduction to Matplotlib
- Introduction to MetPy
- Introduction to Siphon
- Pythonic Data Analysis
- Making maps with Cartopy
- Working with satellite data
- Working with Model data
- Time-series analysis of Buoy Data
Those interested in digging in and writing some code after the workshop are invited to participate in an informal hackathon, which will be held Saturday, March 16th. More details about the hackathon activities will be available at the workshop.
Schedule and Details
The workshop will be held in Kallay-Christopher Hall (1809 Chapel Dr., Valparaiso, IN 46383), Room 210, from 8:30am to 4:30pm on March 14-15, 2019.
For a more detailed schedule with links to the Jupyter notebooks that will be used in the workshop, see 2019 Python Workshop at Valparaiso University.
The workshop cost is $25 for students, faculty, and staff, or $50 for those not associated with an educational institution. Attendees should bring their own laptop if possible; a limited number of laboratory computers are available. (Please contact Dr. Goebbert if you need access to a lab computer.) Total seating is limited to 28 participants.
Contact Dr. Kevin Goebbert.