For sure, the best artists are the ones who take their whole perception of stuff, with the feelings and everything else, and put it directly in someone else's brain. I would maybe say that some data visualization is supposed to do that, particularly data journalism, but definitely not all data visualization.

I think not all data visualization is art in the same sense that not all writing is literature, and in fact almost all isn't, because it's more like "I am in a shared info network with my boss/colleagues/clients/readers, and we need to communicate as rapidly and directly as possible, so we've agreed on a shared visual language that is higher bandwidth." Emails are slightly less exciting to read than a novel but like a million times faster to write per word.

Which is kind of sad. It would be fun to hone that skill and there is no room for that at my job.

(Side note, it seems like everyone always says that the pie chart problem is about lengths vs angles... but isn't it just that one chart has a shared baseline and the other doesn't? Taking the middle out [donut chart] to emphasize arc length doesn't actually solve the problem. Conversely, a stacked bar is more like a pie chart than a bar chart, except with a weird aspect ratio if you only have one stacked bar).

I was too baffled to respond.

It can look pretty, but making it art for the sake of art probably won't resonate with your audience.

That's been my experience after I've trained and consulted with some of the biggest companies in the world.

https://store.metasnake.com/effective-viz

I get that people use the word art as "difficult", "obscure" or "intangible" but...

Art is about self-expression, evoking emotions, and open interpretation. Design is about problem-solving, functionality, and clear communication.

Clearly DataViz is Design.

Pie Charts are good for showing relative proportions of a whole for a relatively small number of items. Donut charts are better because humans tend to misread area slightly in pie charts.

I try to apply principles of progressive enhancement when I want to communicate. I start with plain HTML, basic text block structure and images.

Interactive data viz can be a sublime way to tell a story with data. But if I can't explain the data with the basics, I try to rethink my approach.

I absolutely believe that data visualization, as an art, A craft, can transform the way we share essential ideas.

But I try to make sure a static hero image is up there when necessary.

Maybe the subdivisions with exact numbers also play a significant role in the effectiveness of the bar chart in the article. It lets you compare against a clear reference, so you're often comparing to the scale itself rather than directly between bars.

Are you sure 10% increment guides in bar chart have nothing to do with this?

One area that might be "pregnant" for some new approaches is the visualization of large datasets, eg large graphs. Extracting useful (and objective) information instead of ovewhelming with the sheer number of data points. That is indeed the art of visualisation.

The Wall Street Journal Guide to Information Graphics should be a required for reading for anyone working with numbers.

tldr: only use color when necessary, avoid bold typefaces, keep scales consistent across charts unless there is a specific need to do otherwise.

If the author pops by, I’ve just gotta say: you’re killin it with the cute illustrations, especially the dials one. Very inspiring stuff!

Thanks for sharing, OP.

EDIT: if I had to pick out any one idea for a casual reader to learn about, I’d definitely highlight “Cognitive Load”. It’s used as part of a broader discussion here, but when looked at in a certain light it can capture a whole lot of diverse factors in one consistent framework!

> - Reduce unnecessary cognitive load and emphasize a feeling, as in the Climate Stripes example.

> - Encode a much higher volume of data, as in the Climate Globe example.

> -Add delight and use a visual metaphor to show trends, as in the Coffee Shop example

This the most absurd claim I have ever seen regarding data visualization. Give up precision for delight? Give up precision for a feeling? This article should have been tile "How to lie with graphs". The article is advocating for how to use graphs in the service of rhetoric, not science. This is exactly why visualizing data should NOT be treated as art. The first and third bullet point are obsolutely not reasons to give up