About Beer Analytics
Beer Analytics is a database of beer brewing recipes, built specifically for data analysis. The database currently contains 986,434 recipes, mostly from the homebrewing community. It is made for beer enthusiasts and (home)brewers to provide detailed insights into brewing recipes, even when they're not an expert in data analysis. The goal is to expand the knowledge how certain types of beer are typically brewed, ultimately helping (home)brewers to compose better recipes themselves, and potentially uncover some trends in craft/home brewing.
It as created by beer enthusiast, homebrewer and software engineer Christian Scheb, who was feeling the need to get better insights how certain beers are composed, other than clicking through dozens of recipes. After starting a Jupyter data analysis project for himself in August 2020, he decided build a website from it, so other homebrewers can benefit from these insights alike.
Feedback
I'm happy to hear your feedback about this page. Would you like to see a new chart/metric? Are you missing a feature? Feel free to contact me:
- Create an issue on GitHub
- Send me a Tweet
- Send me a message on Instagram
- Or send me an old-school email: mail (at) christianscheb (dot) de
Tech
This website is built with ❤️ and open source software, using Python and Django for the backend. SQLite is the data storage. Data analysis is performed mostly with Pandas and results are visualized with the fantastic Plotly library. The frontend is built with SCSS and TypeScript for ease of development and is bundled with Webpack.
Contribute
Beer Analytics itself is open source software and available on GitHub. You're welcome to contribute new features, such as new analysis/chart types or bug fixes, by creating a Pull Request on GitHub.