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CRAFT BEER USA: The Artometrics of Craft Beer USA

This report analyzes the TidyTuesday 2018-07-10 release on Craft Beer USA — 2,410 rows after cleaning and merge.

Artometrics Editorial5 min read
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CRAFT BEER USA: The Artometrics of Craft Beer USA
This report analyzes the TidyTuesday 2018-07-10 release on Craft Beer USA — 2,410 rows after cleaning and merge.

This report analyzes the TidyTuesday 2018-07-10 release on Craft Beer USA2,410 rows after cleaning and merge. How bitter and strong is American craft beer — by state and brewery?

Five charts track Abv across time, category, and named entities — trend, leaders, distribution, tiers, and relationships. Where companion files exist in the repo, they are joined before analysis so reception, geography, or metadata columns are not left on the table.

FAST FACTS

2,410Records in the working dataset
0.06Median Abv
0.13Highest observed Abv
Lee Hill Series Vol. 5 - BelTop Name by Abv

DATASET CONTEXT

The source is the TidyTuesday release from 2018-07-10 (R for Data Science community). This working file contains 2,410 rows and 8 columns after merging all available CSV/XLSX tables in the week folder.

Charts are exported as Plotly JSON with PNG fallbacks. Medians are used for robustness where distributions skew. Index-style fields (row numbers, sequential IDs) are excluded from metric selection.

How to read this report: start with the chart caption, then ask what the metric actually means, what a non-expert should notice first, and what an expert would challenge in the source. The goal is not to memorize every number; it is to leave with a sharper question than the one you arrived with.

Reader path: if you are new to the topic, treat each chart as a guided tour of one question: who leads, how concentrated the field is, what changes over time, and where the outliers sit. If you already know the domain, use the same charts as a challenge: check whether the metric is the right proxy, whether the source omits an important population, and whether the headline survives the limitations section.

CHART 1 — BREAKDOWN

Abv by Name

Lee Hill Series Vol. 5 - Belgian Style Quadrupel Ale leads at 0.13; Johan the Barleywine anchors the low end at 0.10.

Grouping by name exposes how the metric varies across the catalog's major entities.

CHART 2 — LEADERS

Lee Hill Series Vol

Lee Hill Series Vol. 5 - Belgian Style Quadrupel Ale leads at 0.130.10 marks the median among the top dozen.

Head-of-field concentration is where quality, scale, or brand visibly separates from the pack.

CHART 3 — DISTRIBUTION

Median 0.06 vs mean 0.06 — the shape is right-skewed

Median 0.06 vs mean 0.06 — the shape is right-skewed.

The top decile begins at 0.08; that tail is where defining cases live.

CHART 4 — CONCENTRATION

The top 5 name entries account for 37% of the aggregate abv

The top 5 name entries account for 37% of the aggregate abv.

Steep Pareto curves mean a small head drives most of the signal — the long tail is noise until it isn't.

SUPPLEMENT — RELATIONSHIP

Abv vs Ibu

Joint plot of abv and ibu surfaces clusters the averages erase.

Bubble size tracks repeat presence — outliers are archetypes, not noise.

LIMITATIONS

Community-cleaned TidyTuesday snapshots are not live APIs. Missing values, spelling variants, and week-of-export coverage limits apply. Merged tables may fan out or duplicate rows when join keys are imperfect.

Findings describe the file on hand — treat them as structural signals about Craft Beer USA, not exhaustive truth about the full domain.

CONCLUSION

Read as a teaching map, Craft Beer USA shows why one metric is rarely enough: leaders, tails, trends, and relationships each answer a different question about abv.

The best reading is modest: use the chart to sharpen the question, then check the source and limits before turning it into a claim.

REFERENCES

Data Science Learning Community. (2018). TidyTuesday: Craft Beer USA. https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2018/2018-07-10/week15_beers.xlsx

EDITOR'S NOTE

Artometrics data report from the TidyTuesday research pipeline. Charts and aggregates are reproducible from the embedded exhibits and public source files.

View TidyTuesday source on GitHub