Location:  Parkville - on campus

This course builds upon a basic knowledge of python (see Introduction to Python - INP) to develop key expertise in scientific applications of python, particularly for the Earth sciences. We will do all of our work within the literate programming environment of jupyter (formerly ipython) notebooks.

We will introduce/review the 'standard' scientific python toolkits such as numpy, scipy, matplotlib, pandas. We will teach you how to manipulate and transform data in simple ways, plotting, mapping, visualisation, interpolation, gridding, function fitting, and exporting data / images into common, interchangeable data formats such as hdf5 and netcdf, geotiff

We will learn how to orchestrate common earth science python software applications including plate reconstruction (pygplates), seismic data set acquisition and analysis (obspy), meshing and interpolation (stripy).

We will learn how to solve very simple differential equations with application to geothermal energy and ground water flow, statistical analysis of data sets, online data repository.


We are going to make extensive use of jupyter notebooks. If you haven't used these before, it will be helpful to watch this tutorial on the benefits of notebooks:  .

You do not need to come along to the course knowing how to use the notebooks, but you should understand why this is a great environment for learning and a springboard to your use of python in the future. 

This article introduces numpy and scipy for users of python [Read the first 5 pages and skim the rest if you wish as this is more detail than you need]

Oliphant, T. E. (2007), Python for scientific computing, Computing In Science and Engineering, 9(3), 10–20, doi:10.1109/MCSE.2007.58. 

We'll be using matplot lib for graphs and cartopy for maps. Please take a look at the gallery for each one and take note if there are any examples that particularly relate to your work or interests: matplotlib and cartopy.

For further information, please see https://handbook.unimelb.edu.au/view/2017/ERTH90051