This portion of the course is focused more on a) some best practices when writing code, and b) doing some slightly more complex data analysis tasks using the Pandas and netCDF4 libraries, visualising them using Cartopy, and animating them using Matplotlib.
The webpage for the first day can be found here.
To get started, follow the directions on the “Setup” page to download data and install a Python interpreter.
| Setup | Download files required for the lesson | |
| 00:00 | 1. Creating Functions |
How can I define new functions?
What’s the difference between defining and calling a function? What happens when I call a function? |
| 00:30 | 2. Errors and Exceptions |
How does Python report errors?
How can I handle errors in Python programs? |
| 01:00 | 3. Defensive Programming | How can I make my programs more reliable? |
| 01:40 | 4. Debugging | How can I debug my program? |
| 02:30 | 5. Working with data using Pandas |
How can I import data in Python?
What is Pandas? Why should I use Pandas to work with data? |
| 03:30 | 6. Working with netCDF files and creating animations |
How can we work with netCDF files (often used in Earth science)?
How can we create maps with coastlines? How do we create lots of figures at once? How can we create animations to help with visualisation? How can we work with datetimes in Python? |
| 05:00 | 7. Next steps |
Where can I go from here?
What are some useful tips and tricks to know when coding? What other opportunities are available for me to learn more? |
| 05:40 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.