**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.

**Pre-reading**

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

- Teacher: Louis Moresi