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Food data

GOAL: Create a service to track real-time USDA produce prices across the 27 major trading produce markets in the US. Aggregate and show data on a mobile app.

  • Python, Objective-C, Swift, Wordpress
  • Analyze and aggregate data from the USDA
  • Scrub and normalize data
  • Show pricing and product data in an easy to understand format
  • Create the marketing website

iPhone Development with big data

This ended up being more of a big-data project. The idea was to collect produce price data from the 13 biggest markets in the USA, clean up that data and present it in an easy to use form for anyone buying produce in bulk.

Buyers could spot trends and decide to buy mass quantities of produce when prices were at lows and farmers/producers would know when they could sell produce at a higher price.

The USDA provides sales information for each market, but they definitely do not make it easy to compare apple to apples so to speak. Produce is sold in cartons, bushels, crates, flats, sacks, containers, jars and bags. Each of those are subdivided down into various sizes like a 45 bushel or a 23 carton or a 50 pound bag. Food is also graded. There’s Fancy, Extra Fancy, US Fancy, etc. There’s differences between markets too, in New York you might buy garlic in a 30 pound carton but in Miami it might be a 5 pound jar. All of that had to be normalized and pushed through an API.

To get new data we had to trigger the entire categorization every time a report was published.

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