This week, Iโve got a little story for you. ๐
A couple of years ago, at a dataviz conference in Portugal, the organizers ran a quick survey. They showed participants a list of chart types and asked two simple questions:
1๏ธโฃ Have you heard of this chart? 2๏ธโฃ Have you ever created one in your career?
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๐ง Hereโs what they found
By the way, this kind of graph is called a dumbbell or Cleveland plot ๐
No surprises for the classics: nearly everyone recognized and had made a histogram.
But check what happened with less common (yet powerful!) chart types!
Take the violin plot, for example. Itโs a fantastic alternative to the boxplot, but only about 20% of attendees had even heard of it ๐ณ. โ I'm not even talking about the Ridgeline chart that is so handy to compare the distribution among several groups.
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What about you ?
Is suggest you test your graphicacy today: how many chart types do you know?
I often give talks to explain my dataviz creation process. And my very first step is listing my options. So knowing the options is fundamental in my opinion.
If any of the chart types in the figure above are unfamiliar, hereโs your next step: visit data-to-viz.com and start exploring! Thereโs always room to grow your dataviz toolkit.
Have an amazing end of weekend, and letโs make some great charts next week!
Cheers,
โ Yan
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PS: By the way, if youโre a Python user and want to learn how to create all these chart types, Iโm working hard on Matplotlib-journey.com. I think youโre going to love it!
PPS: I'll be in Paris on the 11th of December to give a talk. Hit reply if you're around! โ
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