Quantifying Part of the Opioid Crisis

Two weeks ago the Washington Post published a fascinating article detailing the prescription painkiller market in the United States. The Drug Enforcement Administration made the database available to the public and the Post created graphics to explore the top-line data. But the Post then went further and provided a tool allowing users to explore the data for their own home counties.

The top line data visualisation is what you would expect: choropleth maps showing the prescription and death rates. This article is a great example of when maps tell stories. Here you can clearly see that the heaviest hit areas of the crisis were Appalachia. Though that is not to say other states were not ravaged by the crisis.

There are some clear geographic patterns to see here
There are some clear geographic patterns to see here

For me, however, the true gem in this piece is the tool allowing you the user to find information on your county. Because the data is granular down to county-level information on things like pill shipments from manufacturer to distributor, we can see which pharmacies were receiving the most pills. And, crucially, which manufacturers were flooding the markets. For this screenshot I looked at Philadelphia, though I only moved here in 2016, well after the date range for this data set.

It could be worse
It could be worse

You can clearly see, however, the designers chose simple bar charts to show the top-five. I don’t know if the exact numbers are helpful next to the bars. Visually, it becomes a quick mess of greys, blacks, and burgundies. A quieter approach may have allowed the bars to really shine while leaving the numbers, seemingly down to the tens, for tables. I also cannot figure out why, typographically, the pharmacies are listed in all capitals.

But the because I lived in Chicago for most of the crisis, here is the screenshot for Cook County. Of course, for those not from Chicago, it should be pointed out that Chicago is only a portion of Cook County, there are other small towns there. And some of Chicago is within DuPage County. But, still, this is pretty close.

Better numbers than Philly
Better numbers than Philly

In an unrelated note, the bar charts here do a nice job of showing the market concentration or market power of particular companies. Compare the dominance of Walgreens as a distributor in Cook County compared to McKesson in Philadelphia. Though that same chart also shows how corporate structures can obscure information. I was never far from a big Walgreens sign in Chicago, but I have never seen a McKesson Corporation logo flying outside a pharmacy here in Philadelphia.

Lastly, the neat thing about this tool is that the user can opt to download an image of the top-five chart. I am not sure how useful that bit is. But as a designer, I do like having that functionality available. This is for Pennsylvania as a whole.

For Pennsylvania, state-wide
For Pennsylvania, state-wide

Credit for the piece goes to Armand Emamdjomeh, Kevin Schaul, Jake Crump and Chris Alcantara.

The World Grows On and On

I mentioned this this time last year, but I used to make a lot of datagraphics about GDP growth. The format here has not changed and so there is nothing new to look at there. But, the content is still interesting. And the accompanying Economist article makes the point that high growth rates are not always what they seem. After all, Syria’s high growth rate is because its base is so small.

The 2019 GDP growth forecasts
The 2019 GDP growth forecasts

Credit for the piece goes to the Economist Data Team.

Ratings the Foods

For my American audience, Happy Thanksgiving. Coffeespoons will be on holiday for the remainder of the week. But don’t worry, we’ll be back. For my non-American audience, we basically celebrate a tale of the Pilgrims feasting with Native Americans after a successful harvest.

Today’s graphic is really just a series of tables. I think I missed this back in 2016 because, surprise, I had just moved to Philadelphia and was still settling into things—including running Coffeespoons. Anyway, FiveThirtyEight published an article trying to discover the most popular dishes. This is just a sampling , a screenshot of the meats. But you should go check it out to see if your favourite dishes made the cut.

Where's the beef?
Where’s the beef?

Mine did not. I am not a big fan of turkey and am doing a pork roast tomorrow . I guess I could go with the ham in a pinch though.

Credit for the piece goes to Walt Hickey.

Tracking the Charges and Convictions

In case you missed it somehow, the President of the United States, the Leader of the Free World, is now also an unnamed, unindicted criminal co-conspirator in a federal campaign election law case in New York to which his co-conspirator pled guilty.

And you thought Obama’s tan suit was bad.

The guilty plea by Michael Cohen and the eight convictions of Paul Manafort are all part of a growing scandal surrounding the White House. Thankfully the New York Times published a piece highlighting the results of the various trials. In short, the former National Security Advisor has pled guilty, as has a former campaign advisor, a former deputy campaign manager/transition leader/early administration staffer, and another campaign advisor. Throw in yesterday’s news and this table will get longer.

How much longer will the table get?
How much longer will the table get?

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

Going Over (But Actually Under)

Late last week I was explaining to someone in the pub why the World Cup matches are played beyond their 90 minute booking. For those among you that do not know, basically the referees add up all the stoppage time, i.e. when play stops for things like injuries or people dilly dallying, and then tack that on to the end of the match.

But it turns out that after I explained this, FiveThirtyEight published an article exploring just how accurate this stoppage time was compared to the amount of stopped time. Spoiler: not very.

In design terms, the big takeaway was the dataset of recorded minutes of actual play in all the matches theretofore. It captured everything but the activity totals where they broke down stoppage time into categories, e.g. injuries, video review, free kicks, &c. (How those broke out across an average game are a later graphic.)

Through 27 June
Through 27 June

The setup is straightforward: a table organises the data for every match. The little spark chart in the centre of the table is a nice touch that shows how much of the 90 minutes the ball was actually in play. The right side of the table might be a bit too crowded, and I probably would have given a bit more space particularly between the expected and actual stoppage times. On the whole, however, the table does its job in organising the data very well.

Now I just wonder how this would apply to a baseball or American football broadcast…

Credit for the piece goes to David Bunnell.

The London Job Exodus

Brexit is bad for Britain. Here is some proof from an article by Bloomberg that looks at where London-based banking jobs are headed post-Brexit. Spoiler alert, not elsewhere in Britain. The article purports to be more of a tracker in that they will add on data about jobs moving places when news breaks. But I cannot verify that part of the piece.

What I can verify is a sankey diagram. Underused, but still one of my favourite visualisation forms. This one explores where companies’ London-based banking jobs are moving. Right now, it clearly says Frankfurt, Germany is winning.

Look at all those job…
Look at all those job…

As sankeys go, this one is pretty straightforward. Aesthetically I wonder about the colour choice. I get the blues and that the banks are coloured by their ultimate destination. But why the gradient?

But conceptually the big question would be what about London? I probably would have kept London in the destination set. While many jobs are likely to leave Britain, some will in fact stay, and those lines will need to go somewhere in this graphic.

The piece also makes nice use of some small multiple maps and tables. All in all, this is a really solid piece. It tells a great—well, not great as in good news—story and does it primarily through visuals.

Credit for the piece goes to Gavin Finch, Hayley Warren and Tim Coulter.

Down on the Farms

Just a neat little piece today from FiveThirtyEight. They take a look at the potential impact of the Trump administration’s proposed tariffs on the farm vote in the United States. The screenshot of the table shows how the farm population compares to Trump’s margin of victory in 2016.

Farming clearly isn't big in Alaska…
Farming clearly isn’t big in Alaska…

The three states at the top? The very same Pennsylvania, Wisconsin, and Michigan about which we hear so often. Yes, Pennsylvania does have large cities like Philadelphia and Pittsburgh, but agriculture is an important part of its economy. So if the tariffs or the reprisals to the tariffs have any significant impact on the livelihood of farmers, that could be enough, all things being equal, to flip those states.

About the design, I think the inclusion of the mini-bar chart helps tremendously. Tables are great for organising information, but scanning over and through cell after cell of black text can hide patterns. The visualisation of those patterns at the end of each row helps the user tremendously, by making it very clear why those three states were highlighted.

Credit for the piece goes to Rebecca Shimoni Stoil.

Deaths in America

Yesterday was murders in London and New York. Today, we have a nice article from FiveThirtyEight about deaths more broadly in America. If you recall, my point yesterday was that not all graphics need to be full column width. And this article takes that approach—some graphics are full width whereas others are not.

This screenshot shows a nice line chart that, while the graphic sits in the full column, the actual chart is only about half the width of the graphic. I think the only thing that does not sit well with me is the alignment of the chart below the header. I probably would align the two as it creates an odd spacing to the left of the chart. But I applaud the restraint from making the line charts full width, as it would mask the vertical change in the data set.

The screenshot is of the graphic's full width, note the lines only go a little over half the width.
The screenshot is of the graphic’s full width, note the lines only go a little over half the width.

Meanwhile, the article’s maps all sit in the full column. But my favourite graphic of the whole set sits at the very end of the piece. It examines respiratory deaths in a tabular format. But it makes a fantastic use of sparklines to show the trend leading towards the final number in the row.

Loving the sparklines…
Loving the sparklines…

Credit for the piece goes to Ella Koeze and Anna Maria Barry-Jester.

Baseball Is Back

Praise the (baseball) gods.

The 2018 season starts today with I think every team playing—the Red Sox open down in St. Petersburg against the Rays. So today’s post is on the light side as I could not find the awesomest baseball graphic. But FiveThirtyEight did at least preview the season and ran some projections. Naturally, I disagree with their projections. But I think finally this year the Yankees will be more of a threat to the Red Sox than they have been in years. The rivalry is back. (Though it never really went away in my mind.)

Switch numbers one and two and I think this might be okay…
Switch numbers one and two and I think this might be okay…

The above is the screenshot for the American League East, because Boston. But, the rest of the AL is on that page as well. For those of you from my more National League-following cities like Philadelphia and Chicago, FiveThirtyEight also previewed the NL divisions here.

Credit for the piece goes to Neil Paine.

Gerrymandering Pennsylvania Part V

Yesterday we looked at the new congressional district map here in Pennsylvania, drawn up by the state supreme court after the Republican legislature and Democratic governor could not come to agreement.

Also yesterday, FiveThirtyEight explored the redrawn map in more detail to see if, as I’ve read in a few places, the new map is a Democratic gerrymander. In short, no. The article does a great job explaining how, basically, it might seem like it because more Democrats are predicted to be elected based on various models. But, that is only because the map was so extremely gerrymandered in the past that any effort to increase competitiveness or fairness would make Republicans more likely to lose seats.

This one table in particular does a nice job showing just how in an average election cycle there are only four seats that you could consider reliably Democratic whereas there are six that are reliably Republican. And keep in mind that Pennsylvania actually exhibits the reverse split—there are more Democrats than Republicans in the state. So even with this new map, the state exhibits a slight Republican bias.

Still favouring the Republicans
Still favouring the Republicans

Credit for the piece goes to Aaron Bycoffe.