Last Sunday, I posted a data vis crossword puzzle – and I just published the solution.

👉I explain every one of the 60 clues,
👉tell you who won,
👉and talk about how I think that whole crossword adventure went.

I designed a – wait for it –  crossword puzzle this weekend! (Yes, I can't believe it myself.)

I'll send the winner a data vis book of their choice. But I hope it's fun even if you're not in for the price! Here's how to solve it:

I wrote the Weekly Chart today, inspired by (first pic; I learned about it thanks to

Its author said it's unfun to calculate median ages for each congress. So I did exactly that:

What's your favorite Flash ? (....we should take a video/screenshot of now before it's too late?)

I'm trying to answer the question "How colorful is a color?" these days – and I have fun with different models, but don't fully understand them.

Does anyone know a good article/video on colorfulness, or can answer some questions about it (and CIECAM parameters, etc.)? Thanks!

I gave a talk today called "What to consider when considering data vis rules" at the (very enjoyable!) SHOW conference.

Here's the transcript:

Here are the slides:

And here's the 40min talk in 20sec:

Very much looking forward to the SHOW conference this Friday & Saturday, organized by, featuring amazing speakers. I'll give a talk, too, about rules – the conference topic –, starting at 12.45 CET on Friday.

Not too late to sign up:

Thanks to everyone who helps to create result pages for their newsrooms, especially during these times. It's very exciting to see them go live.

Let's collect this goodness.

I spent the past few months to learn more about colors, to finally get rid of the feeling that I'm bad with them. Here I tried to compress some of these learnings (there's more to come):

And that's it! I just published the last part of the series on colorblindness 🎉

Ten of you, incl. cartographers & Mark Harrower, and our Datawrapper CEO told me how it is to be colorblind.

It's enlightening. Read it here:

Yay, it's out: I just published the 2nd part of the colorblindness series, showing ways to visualize data well for colorblind readers.

Expect glyphs, patterns, blue, orange, and me criticizing a popular colorblind-safe color palette:

In the 60 countries with the most COVID-19 cases in total, cases are up: These countries reported more cases in the last seven days than in the week before.

That's crazy and sad and frustrating. So here's an overview. It will update daily on

How many of the data visualizations you created are colorblind-safe? All? 90% at least? Hopefully?

Personally, I don't know.

I wrote a blog post to make you (and me!) care more. It's the first article in a 3-part series on colorblindness. Find it here:

In 5min, the Data Vis Book Club ( ) starts again 🎉
This time with the great – we will discuss his "Data Visualisation Handbook" here:

Even if you haven't read it, come by and ask Andy questions!

Dear peeps, let's discuss: Is it ok to differentiate between categories with lightness, or should we use hues?

Different data viz book authors seem to have different opinions. 1/6

I don't think this chart is particularly useful to understand the data, so I won't include it in our chart collection ( But I do think it offers an interesting perspective on China.

You can get some hover tooltips here:

I created some charts, maps & tables that show the numbers in ...more relative terms. I'm curious what you all think:

👉 Charts I should still build?
👉 Charts I should remove because they're irresponsible?
👉 Data sources I should consider?

The deadline is 🚨 this Sunday 🚨: Apply to learn from the wonderful and/or me during an internship at the charting tool (we build charts! we enable others to build charts, too!). Learn more here:

Impressive comparison between Bloomberg's ad money (green) and other candidates' ad money (darker "on top") by, & for the Washington Post:
But do the non-Bloomberg rectangles on top still count as Bloomberg money? 🤔

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