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Here's the finished version of this #TidyTuesday chart!
📊 Sunburst chart made with #ggplot2 in #RStats
✋ Dropdown interaction added with {ggiraph} with a few little JavaScript helpers
📚 Combined with #QuartoPubYes, you can make interactives in R without requiring Shiny!
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Thanks so much to those who joined me at the Posit Data Science Lab with Libby Heeren and Nick Rohrbaugh!
Here's what I came up with in ~50 minutes of live-coding a #TidyTuesday chart - a parameterised plot, showing which continents twinned cities are from!
A few more things I want to add: tooltips to show city/country names, dropdown to choose a country, and slightly better text contrast!
Code from the lab and resources: https://nrennie.rbind.io/talks/posit-ds-lab/
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An annotation-heavy, faceted area chart for #TidyTuesday this week providing different ways of looking at historic ship production in Italy 🚢
📊 Made in #RStats with #ggplot2
Code: https://github.com/nrennie/tidytuesday/blob/main/2026/2026-05-05
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This week's #TidyTuesday is all about agricultural tariffs in the USA, and I decided to focus in on tariffs on jam 🍓
Of course, that naturally led to figuring out how to write code to plot jam jars in #RStats!
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-04-28
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Day 26 of the #30DayChartChallenge: Trend 📊 (a couple of days early)
A simple chart made with #RStats to show how easy it is to get nice-looking, effective charts with {ggauto}!
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Stockbridge, Edinburgh 🎨
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Day 22 of the #30DayChartChallenge: New Tool 📊
🛠️ Tool: @datawrapper table
🏭 Data: @ourworldindata
💜 With some data wrangling in #RStats -
This week's #TidyTuesday data is all about Global Health Spending 💰️
I created a minimalist world map showing the percentage of health spending on preventive care 📊
Notable upticks in 2021 across many countries, higher % overall in African countries, and lots of missing data
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-04-21
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For this week's #TidyTuesday data on sea bird sightings, there was an obvious choice for which type of bird to focus on - penguins! 🐧
📊 Bubble timeline made with #RStats
🎨 Colours inspired by {palmerpenguins}
📝 Annotations added with {cowplot}Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-04-14
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Day 4 of the #30DayChartChallenge: Slope 📊
⛷️ Slope chart made with #RStats looking at how people interpret the phrases "may happen" and "might happen"
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Day 1 of the #30DayChartChallenge: Part to Whole 📊
🍩 Donut chart made with #RStats showing the percentage of people who rank different terms as more likely than 'likely'
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A little bit of Winter Olympics data art for #TidyTuesday this week! 🎨
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-02-10
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One of my aims for 2026 was to be a little bit less "all or nothing" with projects so I'm pretty proud of my #Genuary2026 contributions!
Still learned lots of new stuff, and had plenty of time left for other things!
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Genuary Day 3: Fibonacci forever
Figuring out how to programmatically create Fibonacci tiles
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I had a great time talking about the process of creating charts with ggplot2 at @rladiesrome tonight! 📊
Slides and code from the session can be found here: https://nrennie.rbind.io/talks/rladies-rome-ggplot2/
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I'm really excited to be running this session for @rladiesrome next month! 📊
We'll be talking about data viz design, building charts in ggplot2, and tips for how to develop your viz skills!
Register: https://www.meetup.com/rladies-rome/events/311324200/
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If you're interested in learning #JuliaLang and are currently an #RStats user (or even if you're not!), then here's a little introduction to getting started! 📊
Blog post: https://nrennie.rbind.io/blog/introduction-julia-r-users/
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It's Day 8 of the #30DayChartChallenge, and the prompt is "Histogram" 📊
💻 Another #RStats + Observable combination ❤️
📈 Kept it simple, but figured out more about small multiples (facets), sorting categories, and colour palettes in Observable today! -
All 31 days of generative art for #Genuary2025! 👇 👇 👇
#Genuary #Genuary2025 #RStats #Rtistry #GenerativeArt #Python