Running elementary.os on a MacBook, what works well, and what does not.

After being disappointed with the direction in which macOS is heading, especially the continuous push into iCloud features that I refuse to use1, I decided to say good-bye to macOS and try elementary.os.

After testing it on a separate desktop computer for a couple of months I finally installed it on my MacBook2. In this post I am documenting my experience for those who might be interested in switching as well.

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  1. most annoyingly the iCloud synchronization of sensitive files that is turned-on by default
  2. 13-inch MacBook Pro from 2015

In Defense of Interactive Graphics

No, interactive graphics are not dead.

It is also not true that “85% of the Times‘ page visitors online simply ignore interactive infographics altogether“.

But since I sort of helped creating1 this confusion, I think it’s time to set this straight:

Interactive graphics are still great, and there are a lot of good reasons to make them!

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  1. The number comes from me measuring the percent of readers who clicked on a prominent button in a couple of graphics we published in 2015. I mentioned the number at a conference, from where it ended up in another talk, then on Medium and finally on FastCo.Design. However, the 85% of readers didn’t ignore the graphic, they just didn’t click the button.

Re-coloring Illustrator graphics based on JSON data files

When working on choropleth maps or charts in Illustrator, sometimes the (final) data is not yet available by the time you’re designing the graphic.

The typical work-around is to re-import the updated part of the graphic and align it with the rest of the artwork. But this is tedious work, especially if you’re dealing with multiple maps.

To address this problem I wrote an Illustrator script that can re-color the artwork based on a JSON file. This blog post will walk you through how to use the script.

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When It’s Ok to Use Word Clouds

tl;dr
It’s ok to use word clouds if your goal is to encourage reading of a large set of otherwise unrelated words that are connected to one or two interesting values (and word count in a text doesn’t qualify as interesting).

This I tweeted yesterday and now I feel that if I encourage the (dangerous) use of word clouds, I have to explain this exception in a little more detail. Why is it sometimes ok to use a widely rejected visualization method, and most times not?

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Look, Ma, No More Mercator Tiles

Using open source tools it is now super easy to make your own map tiles, and with a little extra work you can render them in whatever map projection you want. No more excuses to use Mercator! For example, here is a map we published today at The Upshot. It shows where prime-age women are working more or less then average, and includes data from county-level in the overview map down to every census tract once you zoom in. And all is nicely projected in Albers Equal-Area Conic, a projection widely adopted as standard for U.S. maps.

here’s how you do it


Analyzing bias in opinion polls with R

Never trust a statistic that you
haven’t visualized yourself.

It’s election time in Germany and, as usual, there are tons of opinion polls telling us who is going to win the election anyway. It is debatable whether or not pre-election polls are healthy for our democracy in general, but at least everybody agrees that the polls should be kind of neutral. And if they are not, the institutes publishing the polls should be blamed publicly.

But how do we know if an institute publishes ‘biased’ polls? You guessed it: with data. More precisely: with data and the unique power of data visualization.
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