Enormous insight can be gained from this data set. I decided to take a broad approach by combing the top foods and looking at their prices and inflation throughout the world, region, and country.
This broad approach showed the price of food is greatly determined by nature, rainy seasons, droughts and famines. Additionally, politics plays a great role in food prices. Civil war can make prices skyrocket, and a big push for genetically modified foods can cause prices to go down. Since Africa is prone to both natural and political instabilities, they are suffering greatly from insecure food prices. Also, a stable inflation does not seem to affect food prices nearly as much as high inflation.
The final find was that one countries price does not affect the price of another. Unless these countries share natural disasters such as droughts or famines. The country that is less developed will suffer more.
In the future, I do plan to further improve this analysis by creating and interactive web application to not only analyze the 5 top foods but all contained in this dataset. Also, I want to add statistical model, but I need to spend more time thinking about what I want to gain from this.