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@sponce1.bsky.socialSep 15, 2026, 12:53 AM

📊 #TidyTuesday – 2026 W37 | Dead Sea Scrolls Manuscripts
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #dataviz | #ggplot2

Two-panel dot plot of Dead Sea Scrolls manuscript counts (works with ≥16 manuscripts). Left panel: six familiar biblical books, Genesis at 24. Right panel adds other catalog works — 1 Enoch also totals 24, tying Genesis and exceeding Exodus, Isaiah, and Leviticus, showing the biblical canon captures only part of this collection's textual world.
@jonthegeek.comSep 14, 2026, 4:58 PM

@dslc.io welcomes you to week 37 of #TidyTuesday! We're exploring Dead Sea Scrolls Manuscripts!

📂 https://tidytues.day/2026/2026-09-15
📰 https://www.deadseascrolls.org.il/

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds

Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash.TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.Bar chart showing manuscript copy counts by biblical book, with deuterocanonical books highlighted in orange alongside protocanonical books in blue.
@rladies-bot.bsky.socialSep 14, 2026, 1:26 PM

📝 "Comandos de voz en StarTrek"

Aprendiendo visualización de datos con #TidyTuesday.

👤 Macarena Quiroga

🔗 https://macarenaquiroga.com/post/contribucion-al-tidytuesday-semana-34-comandos-de-voz-en-startrek/

#rladies #rstats #oldiebutgoodie

@rladies-bot.bsky.socialSep 14, 2026, 1:26 PM

📝 "Sliding windows for #TidyTuesday rents in San Francisco"

Master SF rent trends with sliding windows!

👤 Julia Silge (@juliasilge.com)

🔗 https://juliasilge.com/blog/sf-rent/

#rladies #rstats #oldiebutgoodie

@karaman.isSep 13, 2026, 3:16 PM

This week's #TidyTuesday uses the Cappuccino Index by @jameshoffmann.bsky.social. A barista in India works 2h 52m to earn one cappuccino. In Australia, 10 minutes.

Code: github.com/gkaramanis/t...

#RStats #dataviz

Circle pack chart titled "Who can afford the coffee they make?", showing how long a barista has to work to afford one cappuccino in 36 countries, from James Hoffmann's Cappuccino Index. Circles are sized and coloured by that time, and the colour runs from dark blue for the shortest through teal and yellow to dark red for the longest. Two panels split the countries by World Bank income group, each with a small inset world map showing which countries it covers. The middle income panel holds seven countries, led by India at 2h 52m in dark red, then the Philippines 1h 51m, Mexico 1h 15m, Turkey 1h 13m, Malaysia 1h 7m, Argentina 1h and Brazil 57m. The high income panel holds 29 countries and is mostly dark blue. Russia 52m and Chile 49m are the largest, followed by Romania 41m, Greece 36m, Hungary and Portugal 30m, Poland 29m and Czechia 28m. Most of western Europe sits between 14 and 21 minutes. The smallest circles are Australia 10m, Italy 12m and New Zealand 13m.
@mitsuoxv.bsky.socialSep 10, 2026, 12:39 PM

My submission for #TidyTuesday, Week 36 on The Cappuccino Index. I explore cappuccino affordability by continent.

Code: github.com/mitsuoxv/tid...

Boxplot; x-axis is minutes a barista needs to work to afford a small cappuccino, and y-axis is continents (Africa, Asia, Americas, Europe and Oceania).
@nrennie.bsky.socialSep 9, 2026, 12:50 PM

A very quick pictogram for #TidyTuesday this week where we're looking at The Cappuccino Index ☕

#RStats #DataViz #ggplot2

Pictogram chart titled "Italy is one cup ahead," showing how many small cappuccinos a barista can buy with one hour of pay across various European countries. Italy leads at 5 cups, followed by countries like Switzerland, Netherlands, and Germany at 4 cups, down to nations like Romania and Belarus at 1 cup.
@deepalikank.inSep 9, 2026, 5:09 AM

#TidyTuesday week 36 - The Cappuccino Index
#DataViz #Rstats

@rajodm.bsky.socialSep 8, 2026, 9:20 PM

#TidyTuesday 2026 week 35
Mapped the places in France that appear on Castlemap's top 100 global ranking.

Data: Castelmap, curated from Wikidata
Code: github.com/rajodm/TidyT...

#dataviz #rstats #tmap

Map of France (left panel) showing 349 castles, fortresses, and ruins, with 13 highlighted as ranking in Castlemap's global top 100. The 13 sites cluster in 3 regions and are shown in 3 instet maps on the right side of the map: Île-de-France (8, including the Élisée Palace, Palais-Royal, Tuileries Palace, Louvre Palace, Bastille, Luxembourg Palace, Palace of Versailles, and Palace of Fontainebleau), Centre–Val de Loire (3, including Château de Chambord, Château d'Ambroise, and Château de Chenonceau), and Provence-Alpes-Côte d'Azur (2, including Palais des Papes and Château d'If).
@dslc.ioSep 8, 2026, 4:46 PM

It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS

@sponce1.bsky.socialSep 7, 2026, 6:40 PM

📊 #TidyTuesday – 2026 W36 | The Cappuccino Index
.
🔗: stevenponce.netlify.app/data_visuali...
.
#rstats | #r4ds | #dataviz | #ggplot2

Scatter plot titled "Cheap coffee isn't necessarily affordable coffee," plotting mean hourly barista wage against mean cappuccino price across 87 countries on log-log axes, with dashed diagonal lines marking equal work-time cost at 30, 60, and 120 minutes. Pakistan (£1.87 cappuccino, 277 minutes of work) and India (£1.96, 172 minutes) sit far left with cheap coffee but extreme work-time burdens driven by very low wages. Switzerland and Denmark, both averaging £5.41 per cappuccino, require only 14 and 19 minutes, respectively, reflecting high wages. The remaining gray points cluster loosely along the diagonal. Source: James Hoffmann via Filip Reierson.
@jonthegeek.comSep 7, 2026, 4:26 PM

@dslc.io welcomes you to week 36 of #TidyTuesday! We're exploring The Cappuccino Index!

📁 https://tidytues.day/2026/2026-09-08
🗞️ https://www.youtube.com/watch?v=WtlE3BW9Nqs

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds

Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash.TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.Coffee beans.
@mickael.canouil.frSep 7, 2026, 2:04 PM

So much easier to draft and tweak Typst figure (using Gribouille) for TidyTuesday, when working in a Quarto document.

#Typst #Quarto #grammarOfGraphics #TidyTuesday

VSCode window showing a Quarto document on the left panel that shows Typst code cell importing a _plot.typ file and the preview of that file on the right panel
@nrennie.bsky.socialSep 7, 2026, 10:26 AM

If you're at @royalstatsoc.bsky.social conference this week, come along on Tuesday morning at 9am for #TidyTuesday live!

A workshop to help you develop your programming skills, ability to work with data, and be part of a wonderful data community! 📊

#RStats @rssannualconf.bsky.social

Screenshot of first slide of "Developing your data skills"
@karaman.isSep 6, 2026, 1:47 PM

This week's #TidyTuesday is about castles. I mapped the 5,793 castles, fortresses and palaces in Castlemap, from Wikidata. Europe holds 4,083 and Asia 1,280.

Code: github.com/gkaramanis/t...

Six maps titled "Castles of the World", one for each continent, showing the 5,793 castles, fortresses, palaces and ruins that Castlemap gathers from Wikidata. Each landmark is a dot, coloured by the number of other castles within 100 km, dark red where a castle stands alone and orange where many cluster together. All six maps share the same window size, so the continents keep their relative scale. The top row holds North America 167, Europe 4,083 and Asia 1,280, the bottom row South America 113, Africa 144 and Oceania 6. Europe is far denser than the rest and holds the brightest dots, in western Germany, the Netherlands, Belgium, Luxembourg and Czechia. The three countries with the most landmarks are named in each map: the United States 98, Canada 23 and Cuba 11; France 351, Italy 350 and Germany 349; Japan 297, India 156 and China 121; Brazil 78, Chile 15 and Argentina 5; Ghana 31, Egypt 26 and Morocco 25; Australia 3, New Zealand 2 and Tonga 1.
@deepalikank.inSep 5, 2026, 5:56 AM

Does a #TidyTuesday contribution still count if there’s no code, no data, and not a single ggplot() in sight? 😄
another contribution for Week 35 World Castles, I used pen and ink and drew the Tower of London instead.
Still technically a visualization… right?
#DataViz