Cluster analysis of what the world eats

March 9, 2010

(This article was first published on Diego Valle's Blog, and kindly contributed to R-bloggers)

Keeping with the theme of the post below, I used a clustering algorithm to group the different countries according to what they eat. I simply played around with the number of clusters until I got something I thought resembled reality, so don’t interpret this as an in-depth analysis.

  • Group 1: Lot’s of coffee and offal. They don’t like fish and fruits, but eat their veggies. Similar to Group 2.
  • Group 2: Lot’s of calories per day, all kinds of meat, alcohol, milk, butter, potatoes and sugar. Vegetable oils are used for cooking. No beans here.
  • Group 3: Fish and rice (which coincidentally is what I had for dinner yesterday). They use coconut oil and don’t like milk or cheese.
  • Group 4: They like bovine meat, fruits and sugar. They also use palm oil, and don’t like veggies.
  • Group 5: Not many calories per day, lots of starchy roots, beans and pulses.
  • Group 6: Lot’s of carbs (wheat and cereals). They eat their veggies and use olive oil and soybean oil.

The code is here and the data (taken from a database put together by the blog Canibais e Reis) is here.

To leave a comment for the author, please follow the link and comment on their blog: Diego Valle's Blog. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)