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Clinton Sears @clintonsears.bsky.social · 13/05/2026

Twinned or Sister Cities for yesterday's #TidyTuesday My own city has two connections, but there are some super connectors! This maps shows the cities per continent with the most connections, St. Petersburg has 96! Rio has 94! #DataViz #RStats

World map visualization titled 'Nodes of a Connected World' showing over 10,500 sister city relationships globally. Six cities are highlighted as the most connected hubs on their respective continents: Auckland (Oceania), Cairo (Africa), Mexico City (North America), Istanbul (Europe/Asia), Rio de Janeiro (South America), and St. Petersburg (Europe). These six hubs and their 356 key partnerships are shown in distinct colors, while 10,231 additional global sister city connections are displayed as a pale gray network tracing across the continents. The visualization reveals the density and geographic spread of international municipal partnerships, with connection lines creating a complex web linking cities worldwide. A footer shows social media information for Clinton Sears. Data source: Wikidata, curated by bothness/twin-cities on GitHub. Created for Tidy Tuesday, May 12, 2026."

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Clinton Sears @clintonsears.bsky.social · 05/05/2026

I have not done #TidyTuesday for a long time, and this was both fun and challenging! Given my interest in #FiberArts I explored yarn production in Italy. Don't be deceived! The massive spike on the right is still only a tiny amount of yarn produced before and after the war #DataViz #RStats #📊

plot 1 — Wartime Shock and Rebound in Italian Yarn

A stacked area chart showing total Italian yarn output in tons from 1936 to 1985, broken into three categories: Cotton (green), Flock (light gray), and Other (red). The y-axis shows output in tons and the x-axis shows years in five-year intervals. Production was above 175,000 tons before 1940 but collapsed dramatically during World War II, reaching a low of approximately 9,900 tons in 1945. After the war, output rebounded strongly, averaging around 224,000 tons annually from 1950 onward. Cotton yarn consistently makes up the largest share of production throughout the period. Data source: ISTAT (Istituto nazionale di statistica / Italian National Institute of Statistics).

plot 2 — Flock Yarn Dominated, then Faded Away

A line chart showing flock yarn as a percentage of total Italian yarn output from 1936 to 1985. The y-axis shows percentage of total yarn output and the x-axis shows years in five-year intervals. The line rises sharply during World War II, peaking at 71% in 1941 and again at 62% in 1944, likely driven by wartime supply chain disruptions that made this affordable textile technique more attractive. After the war, flock yarn's share declined steadily. By 1966 it had fallen below 10%, and it never exceeded that threshold again for the remainder of the period shown. Two text annotations on the chart highlight these two phases of the story. Data source: ISTAT (Istituto nazionale di statistica / Italian National Institute of Statistics).

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Clinton Sears @clintonsears.bsky.social · 01/05/2026

As a fan of #iNaturalist, I decided to dig into the #citizenscience data regarding three pests impacting our local landscape. It's wild to see how two insects and one tiny nematode can reshape our forests. Big thanks to @vermontpublic.org for the inspiration! 🌳 #Vermont #Rstats Code in Github/viz

Data visualization titled "Expansion of Tree Killing Pests in the Northeast." The image contains a grid of maps showing the Northeast US coastline and inland states. Each map represents a time period, showing a progression of colored dots representing research-grade iNaturalist observations.

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Clinton Sears @clintonsears.bsky.social · 15/04/2026

Will AI-led interviews help mitigate fatigue, and what does this massive dataset imply about thematic saturation? This effort collected >112k interviews, and only ~80k met quality standards, which is a staggering number of interviews discarded #evaluation #datause www.anthropic.com/features/81k...

anthropic.com

What 81,000 people want from AI

Last December, tens of thousands of Claude users around the world had a conversation with our AI interviewer to share how they use AI, what they dream it could make possible, and what they fear it mig...

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Clinton Sears @clintonsears.bsky.social · 04/04/2025

My #30DayChartChallenge Day 4 entry, "The Space Divide: Minimum Chimp Habitat in Zoos and the Wild," looks at the "big or small" theme by comparing minimum cage sizes for #chimpanzees to their expansive natural habitats 🐵 I said I'd use Python but this is #Rstats 😂

The Space Divide: Minimum Chimp Habitat in Zoos and the Wild

The Zoological Association of America (ZAA) only requires 240 square feet of

space for an adult chimp, while the American Association of Zoos and Aquariums

requires 2,000. In the wild, chimps have more than 3,000,000 square feet of

space with their community. This plot doesn't have enough space to show how

massive the chimp territory in the wild truly is.

Data Sources: King, B.J. Animals’ Best Friends: Putting Compassion to Work

for Animals in Captivity and in the Wild (2021) and Fultz et al. How Sanctuary

Chimpanzees (Pan troglodytes) Use Space after Being Introduced to a Large

Outdoor Habitat. Animals (Basel). 2023 Mar 7;13(6):961.

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Clinton Sears @clintonsears.bsky.social · 03/04/2025

Diving into #Vermont wildlife for the #30DayChartChallenge "circle" day! 🦌 Using #Python & #plotly to compare monthly #Moose and #BlackBear sightings 🐻 Data wrangled with #BigQuery and #SQL. Any guesses which animal is seen more consistently throughout the year? 😜 #DataViz #Wildlife #RadialChart

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Clinton Sears @clintonsears.bsky.social · 02/04/2025

Day 2 of #30DayChartChallenge is "slope," and #spottedlanternfly observations on #iNaturalist paint a concerning picture. #Lycormadelicatula is an #invasivespecies that poses a threat to our trees. Join #citizenscientists and report any sightings to help track this pest! #Stats #HitchHikerBug

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Clinton Sears @clintonsears.bsky.social · 01/04/2025

#30DayChartChallenge let's go! This #dataviz was for a bit of #Python practice, and I could *not* have sorted out the non-linear gradient for 1 > n > 0 without #claudeai. Made with #seaborn and patience 🎨 #FractionArt #ColorfulMath #PythonDataViz #FractionFunhouse

$A 10 by 10 heatmap where the y-axis is the numerator, and the x-axis is the denominator. These fractions are shaded--increasingly dark purple for numbers greater than one, white for numbers equal to one (the diagonal of the heatmap), and increasingly dark green for numbers approaching zero.$

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