Melbourne datathon notebooks and data processing scripts.

Manual Setup Steps:

1. Visit https://conda.io/miniconda.html and download the Python 3.6 installer
2. Run the installer, but don't set up the environment. Instead follow these instructions.

Automated Setup Scripts:

1. 'sh basic.sh' <-- this will create the "dthon" Python environment with the basic libraries to load and visualise the data

2. 'sh advanced.sh' <-- this will add more comple scientific and data science libraries for statistical modelling

Using the Environment:

1. Run 'source activate dthon'. This will start you using the environment we just set up.
2. Run 'jupyter notebook'. This will launch a web-based Python environment.

Working with the example notebooks:

Tennessee, Ioanna and Nathan will maintain a set of basic example notebooks in the directory 'notebooks/examples/' to demonstrate basic techniques.

About the directory layout:

•  scripts/ <-- command-line tools to execute a process
  

•  src/ <-- handy methods and functions for re-use
  

•  notebooks/
  

•     examples/ <-- showing based techniques
  

•     <name>/ <-- personal working directories
  

•  submissions/
  

•     <name>/  <-- put your submission files from your experiments here
  

Suggestions for good work practises:

1. Whenever you make a submission that's an improvement, create a copy of that notebook and put a version number on it.