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RADIO STATIONS: The Artometrics of Radio Stations

This report analyzes the TidyTuesday 2022-11-08 release on Radio Stations — 17,186 rows after cleaning and merge.

Artometrics Editorial5 min read
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RADIO STATIONS: The Artometrics of Radio Stations
This report analyzes the TidyTuesday 2022-11-08 release on Radio Stations — 17,186 rows after cleaning and merge.

This report analyzes the TidyTuesday 2022-11-08 release on Radio Stations17,186 rows after cleaning and merge. How do radio formats map across the dial?

Five charts track Frequency 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

17,186Records in the working dataset
101Median Frequency
1,700Highest observed Frequency
WEUPTop Call sign by Frequency
CountryMost common Format

DATASET CONTEXT

The source is the TidyTuesday release from 2022-11-08 (R for Data Science community). This working file contains 17,186 rows and 11 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

Frequency by Call sign

WJCC leads at 1,700; KGED anchors the low end at 1,680.

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

CHART 2 — LEADERS

Top Call sign

WJCC leads at 1,7001,695 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

Frequency by Format

Category boxes reveal whether frequency consensus is shared or contested across tiers.

Wide whiskers flag segments where outliers — not averages — drive reputation.

CHART 4 — GAP ANALYSIS

Frequency vs median by Format

News/Talk sits 1,039 above the median; Contemporary Christian trails by 9.00.

Diverging from the median exposes which tiers over- or under-perform — not just who ranks first.

SUPPLEMENT — CONCENTRATION

The top 5 call sign entries account for 34% of the aggregate frequency

The top 5 call sign entries account for 34% of the aggregate frequency.

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

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 Radio Stations, not exhaustive truth about the full domain.

CONCLUSION

Read as a teaching map, Radio Stations shows why one metric is rarely enough: leaders, tails, trends, and relationships each answer a different question about frequency.

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. (2022). TidyTuesday: Radio Stations. https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2022/2022-11-08/state_stations.csv

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