The Freedom of the Press

By now you may have heard that this Thursday media outlets across the United, joined by some international outlets as well, have all published editorials about the importance of the freedom of the press and the dangers of the office of the President of the United States declaring unflattering but demonstrably true coverage “fake news”. And even more so, declaring journalists, especially those that are critical of the government, “enemies of the people”.

I have commented upon this in the past, so I will refrain from digressing too much, but the sort of open hostility towards objective reality from the president threatens the ability of a citizenry to engage in meaningful debates on public policy. Let us take the clearly controversial idea of gun control; it stirs passions on both sides of the debate. But, before we can have a debate on how much or how little to regulate guns we need to know the data on how many guns are out there, how many people own them, how many are used in crimes, in lethal crimes, are owned legally or illegally. That data, that verifiably true data exists. And it is upon those numbers we should be debating the best way to reduce the numbers of children massacred in American schools. But, this president and this administration, and certain elements of the citizenry refuse to acknowledge data and truth and instead invent their own. And in a world where 2+2=5, no longer 4, who is to say next that no, 2+2=6.

There are hundreds of editorials out there.

Read one from the Philadelphia Inquirer, the Chicago Tribune, the Guardian, and/or the New York Times.

But the one editorial board that started it is that of the Boston Globe. I was dreading how to tie this very important issue into my blog, which you all know tries to focus on data and design. As often as I stand upon my soap box, I try to keep this blog a little less soapy. Thankfully, the Globe incorporated data into their argument.

The end of their post concludes with a small interactive piece that presents survey data. It shows favourability and trustworthiness ratings for several media outlets broken out into their political leanings. The screenshot below is for the New York Times.

Clearly Republicans and Democrats view the Times differently
Clearly Republicans and Democrats view the Times differently

The design is simple and effective. The darker the red, the more people believe an outlet to be trustworthy and how favourably they view it.

But before wrapping up today’s post, I also want to share another bit from that same Boston Globe editorial. As some of you may know, George Orwell’s 1984 is one of my favourite books of all time. I watched part of a rambling speech by the president a few weeks ago and was struck at how similar his line was to a theme in that novel. I am glad the Globe caught it as well.

Credit for this piece goes to the Boston Globe design staff.

Philly Rules

Yo. C’mon, bro. This jawn is getting tired. Just stop already.

If you did not catch it this week, the most important news was Donald Trump disinviting the Super Bowl champions Eagles to the White House to celebrate their victory over the Patriots. He then lied about Eagles players kneeling during the US anthem—no player did during the 2017 season. He then claimed that the Eagles abandoned their fans. Yeah, good luck convincing the city of that.

So naturally we have a Friday graphic for youse.

That's 25,304.
That’s 25,304.

Full disclosure: I root for the Patriots. But I mean, seriously, can’t youse guys do the math?

Turning the Midwest Red

Continuing with election-y stuff, I want to share a fascinating map from the Washington Post. The article came out last week, and it is actually incredibly light in terms of data visualisation. By my count, there were only two maps. The article’s focus is on interviews with Trump voters in 2016 and how their opinions of the president have changed over the last year or so. If you want to read it, and you should as it is very well written, I will warn you that it is long. But, to the map.

I may have used an even lighter shade for 2012 counties…
I may have used an even lighter shade for 2012 counties…

What I loved about this map is how it flips the usual narrative a bit on its head. We talk about how much a candidate won a county in 2016, or even how much the vote shifted in 2016. And anecdotally we talk about “ancestral Democrats” flipping to Trump. But this map actually tries to chart that. It reveals the last time a county actually voted for a Republican presidential candidate—the darker the red, the further back in time one has to go.

Counties that vote Democratic are white, because why do we need them for this examination. Omitting them was a great design decision. Much of the country, as we know or can intuit, voted Republican in 2012 for Mitt Romney. But what about before then? You can see how the upper Midwest, along the Mississippi River, was a stronghold for Democrats with some counties going as far back as the 1980s or earlier. And then in 2016 they all flipped and that flipping was most significant there—of some additional interest to me are the counties in Maine, the Pacific Northwest, and along Lake Erie near Cleveland.

In short, this was just a brilliantly done map. And it sets the tone for the rest of the article, which is interviews with residents of those counties called out on the map.

Credit for the piece goes to Andrew Braford, Jake Crump, Jason Bernert and Matthew Callahan.

Changes to Immigration Enforcement

Almost two weeks ago I read a piece in City Lab that used three maps to look at the changes to immigration enforcement in the first year of the Trump administration. I was taken by this final map in particular.

Some geographic patterns do emerge…
Some geographic patterns do emerge…

While the map does have some large areas of N/A, it still does show some interesting geographic patterns. I think New York showcases it the best. Counties that are less involved in enforcement operations are in the southern part, near New York City. But then you can begin to get a clear sense of what is “upstate” by that break roughly parallel to both the Connecticut and Pennsylvania northern borders.

To a lesser extent you can see the same pattern play out in Pennsylvania. While far more white—as in no change on the map—the counties of orange—more involvement—are located in the interior and western counties. That is perhaps somewhat in the same space as Pennsyltucky.

Immigration is clearly an engaging topic these days, and I found this map interesting not because of its design, but because of the geographic stories it tells.

Credit for the piece goes to Victoria Beckley.

Short and Long Term

One week ago today, President Trump touted soaring stock prices as an indicator of a roaring economy. In truth, stock market prices are not that. They are driven by fundamentals, such as GDP growth, wage increases, and inflation. Furthermore stock prices can be fickle and volatile. Whereas a recession does not begin overnight, the factors build over a period of time, a stock market correction can happen in a single day.

So one week hence, the stock market has seen fully one-third of its gains over the past year wiped out. That is over $1 trillion gone from market funds, 401ks, college saving funds, &c. But again, not to freak people out, these things can and do happen. But because they can and do happen, presidents do not often go touting the stock market as it can come back and bite them.

This morning’s paper therefore had a pleasant graphic to accompany a story about the recent declines. And it was on the front page.

The front page
The front page

Like with the choropleth story I covered a little over a week ago, the graphic in today’s paper was not revolutionary nor earth shattering. It was two line charts as one graphic. What was neat, however, was how it supported two different articles.

One graphic, two articles
One graphic, two articles

But when I looked closer I found what was really neat: context.

Notice the little arrow…
Notice the little arrow…

The chart does a great job of showing that context of adding nearly $8 trillion in value over the course of the administration. But then that sharp decline at the right-side of the chart is blown out into its own detail to show how all was steady until Friday’s economic news was released. I think perhaps the only drawback is how tiny and fragile that arrow feels. I wonder if something a little bolder would better draw the eye or connect the dots between the two charts. Maybe even moving the “… and the last week” line above the chart line would work.

Anyway, I was just curious to see how the charts were depicted on the web. And then lo and behold I was treated to two graphics on the home page. The other is for an article about flood risks to chemical plants, not part of this post. But the focus of our post on the stock market was the same as in print. But here is the homepage with two different graphics, always a treat for a designer like myself.

The New York Times homepage this morning
The New York Times homepage this morning

Credit for the piece goes to the New York Times graphics department.

The Memo

So last week the House of Representatives published a highly controversial memo by Representative Devin Nunes. Why controversial? Because it is apparently missing dozens of pages of additional facts, data, and context. But what the memo does contain are connections between people and things. And this Friday piece from the Washington Post does a good job of trying to explain those connections.

It's just missing a lot of other details…
It’s just missing a lot of other details…

Credit for the piece goes to Darla Cameron, Julie Vitkovskaya, Reuben Fischer-Baum, Ann Gerhart, and Kevin Uhrmacher.

The Shitholes

Today’s post is a very quick reaction to the news last night about President Trump calling Haiti, El Salvador, and African countries “shitholes” and trying to get rid of immigrants from those countries in favour of immigrants from places like Norway.

Norwegian contributions to American immigrants peaked well before the 21st century. At that time, Norway was poor and lesser developed. The data was hard to find, but on a GDP per capita level, Norway was one of the least developed countries in Western Europe. On a like dollar-for-dollar basis, El Salvador of 2008 is not too far from Norway 1850.

I wish I had more time to develop this graphic for this morning. Alas, it will have to do as is.

I'm just really hoping Africa isn't a country again…
I’m just really hoping Africa isn’t a country again…

Trumping (Most) All on Twitter

Initially I wanted today’s piece to be coverage of the apparent coup d’état in Zimbabwe over night. But while I have found some coverage of the event, I have not yet seen a single graphic trying to explain what happened. Maybe if I have time…

In the meantime, we have the Economist with a short little piece about Trump on Twitter and how he has bested his rivals. Well, most of them at least.

Trumping one's rivals
Trumping one’s rivals

The piece uses a nice set of small multiples to compare Trump’s number of followers to those of his rivals. The multiples come into play as the rivals are segmented into three groups: political, sport, and media. (Or is that fake media?)

Small multiples of course prevent spaghetti charts from developing, and you can easily see how that would have occurred had this been one chart. But I like the use of the reddish-orange line for Trump being the consistent line throughout each. And because the colour was consistent, the labelling could disappear after identifying the data series in the first chart.

And worth calling out too the attention to detail. Look at the line breaks in the chart for the labelling of Fox News and NBA. It prevents the line from interfering with and hindering the legibility of the type. Again, a very small point, but one that goes a long way towards helping the reader.

I think the only thing that could have made this a really standout, stellar piece of work is the inclusion of another referenced data series: the followers of Barack Obama. At 97 million followers, Obama dwarfs Trump’s 42.2 million. Would it not be fantastic to see that line soaring upwards, but cutting away towards the side of the graphic would be the text block of the article continuing on? Probably easier for them to do in their print edition.

Regardless, this is another example of doing solid work at small scale. (Because small multiples, get it?)

Credit for the piece goes to the Economist Data Team.

Nambia

C’mon. You knew I was not going to let that one slip by.

President Trump, in a meeting with African leaders, twice name-dropped Nambia and in one mention held it up as having a nearly self-sufficient healthcare system. Funny thing to mention as the US is on the brink of eviscerating its healthcare system. But I digress. The point is that when you are speaking to the president of a country, you take a minute to learn how to pronounce the country’s name correctly. Even write it phonetically in the text if you have to. (I’ve done that.) So where is Nambia?

This was just too too good to pass up…
This was just too too good to pass up…

The Donald and The Donald Subreddit

I don’t use Reddit. But things begin to made sense for me in this article from the Economist as it explained the origins behind Trump’s weird tweet of himself beating up a CNN-headed wrestler.

Unfortunately I don't understand how Reddit works well enough to make full sense of these
Unfortunately I don’t understand how Reddit works well enough to make full sense of these

I think the thing perhaps lacking from the graphic is a line that tracks Trump’s approval or popularity. The article mentions that explicitly and it would be interesting to see that track over time. Although I certainly understand how stacking so many line charts above each other could become difficult to compare.

And my final critique are the Election Day outliers. They are above the y-axis maximum. But I wonder if there couldn’t have been a way of handling the outlier-ness of the datapoints while remaining true to the chart scales.

Credit for the piece goes to the Economist graphics department.