Readme.txt

TASK description:

Given the ​Olympic History​ dataset from Kaggle:
1. Read the data using any method of your choice.
2. Analyse the data and produce statistics and insights that you consider useful or
noteworthy. It is up to you to choose features, statistics and methods for your
analysis.
3. Create a visual report of your analysis.
You are free to use you favourite tools, such as Jupyter Notebooks, or Python scripts to generate visualisations that are subsequently knitted into HTML or LaTeX.
There is no right or wrong answer in this task, and your assessment does not have to be very complex, but we expect
1. Meaningful, interesting, and insightful analysis
2. Good quality, well organised code.

SOLUTION:

My solution consists of 5 jupyter notebooks: 4 notebooks labelled sequentially in order in which they should be seen, and an Appendix notebook. This can be omitted, but sequentially it sits between notebooks 2 and 3.

Notebook 1. Contains the initial data checks and cleaning
Notebook 2. Contains a mini review of findings already made by other people, extended inlaces by my own analysis or commentary.
Notebook 3. Contains takes a closer look at ‘Europe in the Olympics’
Notebook 4. Attempts to predict if an athlete will win a medal using machine learning. 

Notebooks 2 and 3 contain code toggle on/off buttons which improve readability. The default if for the code to be off. 

The folder also contains a presentation of the key results in two formats