Introduction

It is 35 degree Celsius out side, we are in the middle of the ‘slow news season’, in many countries also called cucumber time.  A period typified by the appearance of less informative and frivolous news in the media.

Did you know that 100 g of cucumber contain 0.28 mg of iron and 1.67 g of sugar? You can find all the nutrient values of a cucumber on the USDA food databases.

Food Data

There is more data, for many thousands of products you can retrieve nutrient values through an API (need to register for a free KEY). So besides the cucumber I extracted data for different type of food for example

• Beef products
• Dairy & Egg products
• Vegetables
• Fruits
• etc.

And as a comparison, I retrieved the nutrient values for some fast food products from McDonald’s and Pizza Hut. Just to see if pizza can be classified  as vegetable from a data point of view So the data looks like:

I have sampled 1500 products and per product we have 34 nutrient values.

Results

The 34 dimensional data is now compressed / projected onto a two dimensional plane using UMAP (Uniform Manifold Approximation and Projection). There is a Python and R package to this.

An interactive map can be found here, and the R code to retrieve and plot the data here. Cheers, Longhow.