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572 results for “nrennie”
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Since this chart type is a little bit unusual, here's a little scrollytelling explainer of how to read this chart!
Link: https://nrennie.rbind.io/scrollytelling/posts/sustainable-energy/
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Since this chart type is a little bit unusual, here's a little scrollytelling explainer of how to read this chart!
Link: https://nrennie.rbind.io/scrollytelling/posts/sustainable-energy/
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Since this chart type is a little bit unusual, here's a little scrollytelling explainer of how to read this chart!
Link: https://nrennie.rbind.io/scrollytelling/posts/sustainable-energy/
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Since this chart type is a little bit unusual, here's a little scrollytelling explainer of how to read this chart!
Link: https://nrennie.rbind.io/scrollytelling/posts/sustainable-energy/
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Since this chart type is a little bit unusual, here's a little scrollytelling explainer of how to read this chart!
Link: https://nrennie.rbind.io/scrollytelling/posts/sustainable-energy/
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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An alternative way of comparing two distributions for #TidyTuesday this week! 📊
The diameter of each arc shows the % with access to non-solid fuels, split by urban and rural areas ⛽
Code: https://github.com/nrennie/tidytuesday/tree/main/2026/2026-05-26
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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Managed to get {ggchord2} working with {ggiraph} so you can* have interactive chord diagrams with tooltips!
*currently a bit hacky but technically does work
Example: https://nrennie.rbind.io/data-viz-projects/local-council-elections/
This example is a remake of a Sankey chart published by YouGov today in this article: https://yougov.com/en-gb/articles/54811-labours-voter-coalition-broke-more-to-left-than-right-at-2026-local-elections
Original Sankey chart: https://flo.uri.sh/visualisation/29040587/embed
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If you have (or are thinking about) moving away from GitHub, GitLab is one alternative. If you're a regular #QuartoPub or #RStats user, you might find it hard to find information about how those work with #GitLab.
So here's a blog post showing you a few different ways to deploy Quarto documents with GitLab Pages!
(Featuring penguins 🐧obviously )
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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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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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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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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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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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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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📊 Five #ggplot2 functions I wish I'd known about earlier 📊
I've written a short blog (with examples) of some of the lesser-known {ggplot2} functions and arguments that make it easier to create better charts!
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You can find the resources from yesterday's "No more copy and paste! Parameterized plots and reports with #RStats and #Quarto" R/Medicine workshop online!
Lots of interesting questions in the workshop chat, especially around collaborative editing! I've uploaded some more resources and answers to some of the questions in the "Resources" tab of the workshop.
Link: https://nrennie.rbind.io/r-medicine-2026-parameterized-reports/
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I had a great time at @EdinbR last night, talking about interactive charts in R 🦖 (and catching up with people I haven't seen in a while)
💬 How to add tooltips and dropdowns
🦒 In R with {ggiraph}
📊 By passing data from R to ObservableSlides: https://nrennie.rbind.io/talks/edinbR-interactive-charts/slides.html
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Quarto + #RStats + Observable = ❤️
New blog post from me about:
👁️ What is Observable?
❓ Why should R users care?
📊 How do you use both together to make interactive charts?