Category: Analysis

Sorry, XKCD, pink is not the best-tasting color

XKCD is the best-tasting webcomic, with a penchant for data-driven comics that are both funny and informative.  So I was excited to see this recent comic, showing the best-tasting colors. I quickly realized that I had, at my fingertips, a dataset that could corroborate this comic. The What to Brew dataset has roughly 118,000 datapoints of […]

When algorithms drink beer

Last year, the BJCP released a new set of beer style guidelines that regrouped and reclassified the world of beer into styles and categories. This was based on a lot of hard work by some very smart people. So of course, I wanted to see how a computer could compare. For this exercise, I am using […]

Homebrew addition clustering

There are currently well over 100,000 votes on What to Brew, meaning it’s a treasure trove of data. But data is only as useful as its analysis. This article looks at my work to find groupings of similar homebrew additions based on how well they work with each style. I decided to use k-means clustering to […]

What are “Similar Additions”?

You may have noticed, while perusing the rankings of different additions, a small section called “Similar Additions”. This is a pretty fun feature that adds a lot of possibilities. How it works This is the boring part, unless you love data. Basically, I wrote a script that goes through each addition, and compares how it’s rated […]

How What to Brew works

How in the world did I come up with a juniper berry gose? Is a Chai Saison actually good? A Hazelnut Belgian Tripel? How does this site work? Great questions. Here’s a bit of what goes on behind the scenes on this site. First, What to Brew collects a ton of data. Through our website […]