Two radar charts side by side. On the left, the nine values are in descending order, forming a type of snail shell figure. On the right, the nine values are in random order, forming an explosion-like shape. These charts have the same values – just in a different order Two radar charts side by side, illustrating how the ordering of axes in a radar chart dramatically changes the perceived shape — even when the underlying data is identical. Both charts show scores for Jane Doe (blue) and John Doe (pink) across nine dimensions labelled A through I, with values ranging from 0 to 100. Jane Doe's chart shows a compact, roughly rounded shape sitting mostly in the upper half of the radar, suggesting her high scores are clustered around adjacent axes in this arrangement. John Doe's chart shows a jagged, star-like shape with sharp spikes extending outward in several directions and deep indentations between them, creating a visually fragmented appearance. The key insight of this chart is that both shapes represent exactly the same set of values — only the order of the axes differs. This demonstrates a well-known limitation of radar charts: the visual shape is highly sensitive to axis arrangement, which means two identical datasets can look completely different depending on how the axes are ordered. Readers should focus on individual axis values rather than overall shape when interpreting radar charts. Left: Jane Doe Right: John Doe Created with the Radar chart template

Nice reminder and visual representation of the limitations of radar charts, by Flourish 📊

Source: flourish.studio/blog/create-...

Someone trying to flex their data viz skills, totally lost in the sauce: some kind of goofy arc thing

Someone trying to actually communicate quantitative information visually: dumbbell plot

Are the data proportional to petal length or to area?

The scoundrel who came up with the frequency interpretation of probability.

Isn't CRAN supposed to reject updates that break downstream packages?

Minard Day 2021: Resources, Research and Inspirations Michael Friendly

📊 #OTD 🎂🎂🎂
Happy Minard Day!
Charles Joseph Minard's, b. Mar 27, 1781, his big 245th. #OTD #dataviz

One way to celebrate is to visit @infowetrust.com wonderful
Visual Catalog of the Work of Charles Joseph Minard,
bit.ly/3lOXsbR

Another is my celebration of Minard Day, 2021 ed, bit.ly/49f7k1t

A dozen year ago, I was alone at home and decided to treat myself to a beer and a detailed exploration of the famous Minard map. I wrote this blog post, which is still one of the most popular on our website all these years later. 📊

chezvoila.com/blog/minard-...

No.

@newyorker.com Thanks for dark mode. Could you fix basic text rendering next?

How far can you get in 60 minutes? European cities offer vastly larger areas reachable by public transit than US cities of comparable population size. Source: lconwell.github.io/lucasconwell...

I wonder what this looks like using the first half of the viridis magma palette.

See also: Blank Space by David W. Marx, which argues that aesthetic fragmentation and other forces have resulted in 21st century cultural stagnation.

Why do people mention which slop bot made something for them? Brand loyalty? Why not say nothing and let people think you used your own knowledge and abilities?

Introducing AI in RStudio Today we’re introducing AI in RStudio. We’ve embedded a specialized agent directly into RStudio so it can read your live session context and provide more accurate assistance for data science and analy...

Posit is so embarrassing.

Thumbnail from a review of a "dataviz for kids" book.

What is with all the "📊 for kids" books lately?

Is it just slop bots driving the cost of illustration to zero?

Do parents really buy these to read to their kids? Is it a résumé padding exercise for the authors?

160 CAD for the hardcover!?

Juxtaposed horizontal bar graphs using slightly different scales.

"Nothing is lost by adding the second graph."

Sure, except for a consistent scale. 📊

Cantor's theorem is 135 years old. How much longer until it has been sufficiently communicated to the public?

The StatsCan website is baffling.

Every dataviz product is meticulously documented with authorship, update cadence, underlying datasets, keywords, related outputs... everything but a link to the actual viz! 📊

Once you know to look out for conditioning on the outcome, you see it sneaking up on you around every corner!

I wonder whether the categorization of farmers into "large" and "small" in the data used for this visualization 📊 of income inequality in 19th c. France amounts to conditioning on the outcome. Or maybe it's by acreage?

freerangestats.info/blog/2026/02...

From the first and second editions of @rmcelreath.bsky.social's Statistical Rethinking. 📊

I'm guessing this is with the water already at a full boil, which is never how I cook pasta.

I guess the orange line starts past combat age so it must be.

Those born in 1919 were the right age to die in WWII, or is that already accounted for here?

A chart with overlapped bars.

Am I wrong to think that overlapping bars is just straightforwardly an error? Now area (and thus visual impact) is no longer proportional to the data. Maybe I'm too VDQI-pilled? #dataviz 📊

(Chart from SWD: Before & After)

Well, @newyorker.com... is this "re-signed" or "resigned"? Why leave this at a line break? You'll use the dieresis but not the double hyphen?

The first portrait of Gutenberg appeared 99 years after his death, so the likeness here is, unfortunately, just a guess at what he might have looked like.