Keywords: Brewing, beer, yeast, visualisation, summary statistics
Webpages:
https://dynamobrew-stats.shinyapps.io/WhiteLabsBrewAppHb/ How is
R helping brewers to choose the best yeast for their beer? How does yeast choice influence predicted quantities like bitterness versus measured bitterness?
This is meant as a short, fun presentation, touching on Beglian brewing heritage.
I will present walk-through of an interactive
shiny app I created for a client in the brewing industry.
The initial task was primarily to ingest the data and produce an interactive enviroment, where the client’s employees could explore their data. I will not spend too much time on this, but will mention briefly the database technologies used to access the data. I will mention some of my experiences with productionalised a full data flow (ingestion, transformations, outlier handling, visualisation).
The main goal of the presentation will be to visually demonstrate differences between beer styles with regard to their recipes, and to demonstrate the importance of matching beer style with an appropriate yeast.
Before the Conference, I plan on implementing a clustering method based on Self-Organising Maps. This should be a very nice way to explore the natural clustering of recipes – and it should map very neatly to beer styles.
Pending approval from RateBeer, I will also join some high level beer styles data scraped from the
https://www.ratebeer.com website over the brewing yeast data.
