Python for climate scientists

Initially forked from https://github.com/SciTools/courses this course is intended to provide a thorough grounding in Python for those working in the earth sciences.

Note that Day 2 of this course was taught to the Oxford University NERC DTP as part of 'Large data analysis' November 2016.

This notebook covers assorted Python 'hints and tips' of differing difficuluty, and which aren't all covered in the course: https://nbviewer.jupyter.org/github/duncanwp/python_for_climate_scientists/blob/master/course_content/notebooks/hints_and_tricks.ipynb?create=1

Additional Python resources can be found here: https://github.com/duncanwp/python_for_climate_scientists/blob/master/resources.md.

The course itself is split into three days:

Day 1

Python 101

2 hours notebook

An introduction to numpy

2 hours — depends on a basic Python background notebook

An introduction to matplotlib

1.5 hours — depends on "An introduction to numpy" notebook

Cartopy in a nutshell (for Iris)

1 hour — depends on "An introduction to matplotlib" notebook

Day 2

An introduction to Iris

3 hours — depends on "An introduction to numpy" notebook

An introduction to CIS

3 hours — depends on "An introduction to Iris" and "An introduction to matplotlib" notebook

Day 3

Optimisation and an introduction to PyCharm

1.5 hour notebook

An introduction to Object Oriented concepts

0.5 hour notebook

Examples of object-oriented programs

1 hour barotropic model

Exception handling

0.25 hour notebook

Basic testing

0.5 hour materials

F2Py

0.75 hour notebook

Pandas

0.5 hour — depends on "An introduction to CIS" notebook