The Sinking City of Jakarta

Everyone is probably familiar with Venice, slowly sinking below the Adriatic. But, did you know the city of Jakarta, Indonesia is also sinking?

The BBC published an informative article about the city’s looming problem and the piece includes several nice graphics. The screenshot below is an interactive timeline of the amount of subsidence, or sinking, in the the Jakarta region. It’s been notably worst along the coast. But the striking part are the forecasts for 2025 and 2050 that place the city in danger.

The coastline at the north has experienced the worst of it
The coastline at the north has experienced the worst of it

Photography of the scale of the subsidence feature throughout the story. And about halfway through is a nice motion graphic piece that attempts to explain the sinking. I am not certain it is the best graphic, after all it references two US NBA stars and I wonder how well known they are. (Whereas everyone clearly knows who David Ortiz is.)

I was aware of Jakarta’s peril, but until reading this article, I had not realised just how imperiled the city really is.

Credit for the piece goes to the BBC graphics department.

T Minus 12 Weeks

Today is Tuesday, 14 August. We are now 12 weeks away from the 2018 midterms. That is just three months away. Coverage will only intensify in the weeks to come, and you can be certain that if there are pieces worth noting, I will do that. But to mark the date I went with this choropleth map from the New York Times.

The nation will turns its eyes to you…in 12 weeks
The nation will turns its eyes to you…in 12 weeks

Nothing too crazy here. Likelihood of results colour the districts. The darker the blue, the more solid the Democratic seat. The darker the red, the more solid the Republican one. But what this map does really well is it excludes the likely’s and the solids and sets them to a light, neutral grey. You can still hover over a district if you are curious about where it falls, but, in general those have been excluded from the consideration set because they are not the districts of the most national attention.

Secondly, note the state labels. States like Wyoming that have no competitive seats have no label. After all, why are we labelling things that have no impact on this story, again, the competitive races. Fewer labels means fewer distracting elements in the graphic.

Finally, the piece includes the ability to zoom into a region. After all, for those of us living in urban areas, our districts are geographically tiny compared to the at-large or state-wide seats like in Wyoming, the Dakotas, and Alaska. Otherwise, good luck trying to find the Illinois 5th or Pennsylvania 3rd.

Credit for the piece goes to Jasmine C. Lee.

Ohio 12th Results

Last week parts of Ohio voted for a special election in the 12th Congressional District. Historically it has been a solidly Republican district by margins in the double digits. However, last week Republicans barely managed to hold the seat by, at the latest count I saw, less than one percentage point. Why? Well, it turns out that Republican support is bleeding away from one of the traditional strongholds: suburban counties.

I saw this data set late last week on Politico and I knew instinctively that it needed to be presented in another form than a table. Consequently I sketched out how it could work as small multiples of area charts to highlight just how Republican the district is. This is the digitisation of that take. Unfortunately my original sketch also featured a map of the district to show how this falls to the north and east of the city of Columbus. But I did not have time for that. Instead, I sketched up something else, but I need time to work on that. So for now, this concept will have to suffice.

That flip to the Democrats in Franklin County could be  a problem come November
That flip to the Democrats in Franklin County could be a problem come November

Credit for the piece is mine.

Radiohead in Philadelphia

A week and a half ago my favourite band, Radiohead, played two shows in Philadelphia to close out their 2018 North America tour. I got to see the final of the two shows. And I decided to make this little piece over the weekend. Because it was totally fantastic.

The data shows that the band played a good mix of songs from across their discography. Admittedly they played nothing from Pablo Honey, but with the exception of Creep and Anyone Can Play Guitar along with some of the era’s b-sides, I really do not listen to that album all that often. They also skipped over Amnesiac, but did play five songs from my favourite album, Kid A, so, yeah, again, totally fantastic. Especially those final three songs to close the main setlist. Just brilliant.

Two hours of amazing
Two hours of amazing

Credit for this work is mine.

Joblessness in the Developed World

  • We have been looking at tariffs a little bit this week, but unfortunately one of the side effects of tariffs is job losses. And of course when it comes to people losing jobs, not all countries in the  developed world handle them the same. Last month the Washington Post published an article examining how those countries compare in a number of related metrics such as unemployment compensation, notice for termination, and income inequality.
Not all countries give people the short stick.
Not all countries give people the short stick.

It uses a series of bar charts to show the dataset and reveal how the United States fares poorly compared to its peers. The chart above looks at the earning needed for termination from employment and the differences are stark. The outlined bar chart shows longer tenured employees and the full bars as coloured. Of course this makes it look like a stacked bar chart or filled bar chart. Instead I wonder if a dot plot would be clearer. It would eliminate the confusion in determining what if any share of the empty bar is held by the full bar.

The US offers shockingly little assistance to people
The US offers shockingly little assistance to people

The chart for unemployment insurance versus assistance is a bit better. Here the bar represents insurance and the lines assistance. I like how the lines continue off beyond the margins to indicate an unlimited timeframe for assistance. However, for those countries where assistance is short-lived, the bars versus lines again begin to look like an instance of a share of a total, which they are not.

My New Toast

I am a millennial. That broadly means I am destroying and/or ruining everything. It also means I am obsessed with things like avocado toast. It also means I am not buying a house. Thankfully the Economist is on top of my next fad: indoor houseplants.

Plant things
Plant things

Your author will admit to having a few: a hanging plant, an Easter lily, an aloe plant and its children, and a dwarf conifer. Just don’t ask me how they’re doing. (Hint: not well.) Turns out I am not a plant person.

In terms of the graphic, though, what we have is a straight up set of small multiples of line charts. The seasonality mentioned in the article text appears quite clearly in a number of plants.

But is Swiss Cheese really a plant?

Credit for the piece goes to the Economist Data Team.

Apple Hits One Trillion

Last Tuesday we looked at a print piece from the New York Times detailing the share price plunge of Facebook after the company revealed how recent scandals and negative news impacted its financials. Well, today we have a piece from last week that shows how large Apple is after it hit a market capitalisation of one trillion US dollars.

The piece itself is not big on the data visualisation, but it functions much like the Facebook piece, as a blend of editorial design and data visualisation. The graphic falls entirely above the fold and combines a factette and maybe we could classify it as a deconstructed tree map. It uses squares where, presumably, the area equates to the company’s value. And the sum total of those squares equals that of one trillion dollars, or the value of Apple.

Looking at the full page
Looking at the full page

In terms of design it does it well. The factette is large enough to just about stretch across the width of the page and so matches the graphic below it in its array of colours. Why the colours? I believe these are purely aesthetic. After all, it is unclear to me just what Ford, Hasbro, and General Mills all have in common. In a more straight data visualisation piece, we might see colour used to classify companies by industry, by growth in share price or market share. Here, however, colour functions in the editorial space to grab the reader’s attention.

The design also makes use of white space surrounding the text, much like the Facebook piece last week, to quiet the overall space above the fold and focus the reader’s attention on the story. Note that the usual layout of stories on the page continues, but only after the fold.

When we keep in mind the function of the piece, i.e. it is not a straight-up-explore-the-data type of piece, we can appreciate how well it functions. All in all this was a really nice treat last Friday morning.

Credit for the piece goes to Karl Russell and Jon Huang.

Always Be Creating

I like to think that becoming a good designer requires lots of work. And that means different types of work. Work pushing you to learn new skills. So this graphic by Jessica Hagy over on Indexed makes perfect sense. How good you at something ties into how much you work at it.

Got to get through the x to get to the y
Got to get through the x to get to the y

I pair the concept with Glenngarry Glen Ross and Alec Baldwin’s “Always be closing” speech. For your Friday entertainment, this is my more favourite rendition of it: https://www.youtube.com/watch?v=J_vSirIJEsY&t=7s 

Credit for the piece goes to Jessica Hagy.

Fundraising for the Midterms

We are now less than 100 days away—95 to be exact—from the 2018 midterm elections here in the United States. As we get closer and closer we not only get more information from polls, but also campaign finance reports. Those can sometimes serve as a proxy for support as lots of grassroots support can dump lots of cash in a candidate’s war chest. Wheras a candidate who drums up little support might find him or herself with scant funds to fight the campaign.

So what does that funding tell us right now? Well last week Politico posted an article looking at that data. They broke the dataset into chunks by the likelihood of the results. This screenshot is of Pennsylvania’s 1st Congressional District.

What's going on north of Philly
What’s going on north of Philly

Each district is represented by a dot plot, with the total money raised by each candidate plotted, the distance in grey being the amount by which the Democrat outraised the Republican.

This is a nice piece as the hover state provides a nice grey bar behind the district to focus the user’s attention. Then for the secondary level of information in terms of cash on hand for the Democrats, i.e. who has cash now, we get the dot filled in versus the open state for simply money raised. Then of course the hover state reveals the actual numbers for the two candidates along with the difference between the two.

The funny thing with this particular district, the Pennsylvania 1st, is that Wallace is not necessarily raising a lot of money. He is a self-funding millionaire. He also is not the most electable Democrat in a competitive seat. It will be fascinating to watch how this particular district performs over the next few months, but most importantly in November.

Credit for the piece goes to Sarah Frostenson.

Development Languages

Last week the Economist published an article sort of about my industry. Now I am a designer and more familiar with the front-end design and some HTML and CSS, but a lot of the things I have designed over the last few years have needed some serious developers with some serious skills. And those guys were the ones who would truly understand this graphic, which looks at the popularity of Python relative to other languages like C++, Java, Javascript, .NET, &c.

Python has certainly climbed in importance
Python has certainly climbed in importance

I really like what the designers did here. First and foremost the key chart is a ranking chart showing the popularity of languages since 1988—Java and C have consistently been at the top. But other languages no longer relevant are not even shown. (Where are you, Actionscript?) Those that are both relevant and also mentioned are colour coded within the set.

But the truly nice thing is being able to use the empty space of the lower-left area of the chart to add some context. It shows the growth in Google searches since 2010 in searches for Python.

Bonus note, look at that rise in R since 2008.

Credit for the piece goes to the Economist Data Team.