<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Craft-Beer on DATATWEETS</title><link>https://datatweets.com/tags/craft-beer/</link><description>Recent content in Craft-Beer on DATATWEETS</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2026 Datatweets</copyright><lastBuildDate>Wed, 08 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datatweets.com/tags/craft-beer/index.xml" rel="self" type="application/rss+xml"/><item><title>Python Dictionaries in Practice: Building Lookup Tables with Craft Beer Data</title><link>https://datatweets.com/tutorials/python-dictionaries-craft-beer/</link><pubDate>Wed, 08 Jul 2026 00:00:00 +0000</pubDate><guid>https://datatweets.com/tutorials/python-dictionaries-craft-beer/</guid><description>Dictionaries aren&amp;rsquo;t just key-value pairs — they&amp;rsquo;re how you join, count, and group data without a library. This tutorial uses a real craft beer dataset (2,410 beers, 558 breweries) to build a lookup table that joins two CSV files, then counts, groups, and summarizes with nothing but built-in Python.</description></item></channel></rss>