iPhone Screen Size

Your humble author has returned. And on my trip up to Boston I took plenty of photos with my Nexus 5X, a Google-designed smartphone. That is correct, this designer does not use an iPhone. But I am aware of the latest things coming out of Apple—after all this is being typed up on a Mac—and so the larger screen size caught my attention.

The Economist put together a piece looking at the screen sizes of the iPhone models over the years and then used that to project into the future the likely sizes of the phone’s display.

Bigger, and bigger, and bigger, and…
Bigger, and bigger, and bigger, and…

Now the article hints at what I would be particularly interested in: the screen sizes of comparable Android models. How have they changed over the years? I still cling to my smaller screen size mobile as I am not a fan of the phablet.

The chart itself is simple and well done, plotting the models without any fuss. But the most important part is the benchmark line of the iPad mini’s screen size. And the user can clearly see the forecast merger of the sizes.

Credit for the piece goes to the Economist Data Team.

Europe’s Far-right Parties

Yesterday we looked at the rise of the far-right in Sweden based on their electoral gains in this past weekend’s election. Today, the Economist has a piece detailing their strength throughout Europe and they claim that this type of nationalist party may have peaked.

The tile map, though
The tile map, though

The graphic fascinates me because it appears to be a twist on the box or tile map, which is often used to eliminate or reduce the discrepancies in geographic size so that countries, states, or whatevers, can be examined more easily and more equitably.

I am guessing that the ultimate sizes, which appear to be one to four units, are determined by population size. The biggest hitters of Germany, the UK, France, and Spain are all four squares or boxes whereas the smaller states like Malta are just one. (But again, hey, we can all see Malta this time.)

I think this kind of abstraction will grow on me over time. It is a clever solution to the age-old problem of how do we show important data in both Germany and Malta on a map when Malta is so geographically small it probably renders as only a few pixels.

On the other hand, I am not loving the line chart to the right. I understand what it is doing and why. And even conceptually it works well to show the peaks of the parties. However, there are just a few too many lines and we get into the spaghettification of the chart. I might have labelled a far fewer number and let most sit at some neutral grey. Or, space permitting, a series of small multiples could have been used.

Credit for the piece goes to the Economist Data Team.

Which of These Countries Does Not Belong

For those of you reading from the States, I hope you all enjoyed your holiday. And for my UK readers, I hope you all enjoyed your summer bank holiday last weekend. So now to the good and uplifting kind of news.

Something is clearly not right here.
Something is clearly not right here.

Indeed, a chart about deaths from firearms from the Economist. From a graphical standpoint, we all know how much I loathe stacked bar charts and this shows why. It is difficult for the user to isolate and compare the profiles of certain types of firearm violence against each other. Clearly there are countries where suicide by gun is more prevalent than murder, but most on this list are more murder happy.

And then the line chart that is cleverly spaced within the overall graphic, well, it falls apart. There are too many lines highlighted. Instead, I would have separated these out into a separate chart, made larger, so that the reader can more easily discern which series belongs to which country. Or I would have gone with a set of small multiples isolating those nine countries.

I am also unclear on why certain countries were highlighted in the line chart. Did they all need to be highlighted? Why, for example, is Trinidad & Tobago. It is not mentioned in the article, nor is it in the stacked bar chart.

But the biggest problem I have is with the data itself. But, every one of the countries on that list is among the developing countries or the least developed countries. Except one. And that, of course, is the United States.

Credit for the piece goes to the Economist Data Team.

The Rise of Online Dating

This past weekend I cited this article from the Economist that looked at the rise of online dating as a way of couples meeting. There was some debate about which channels of interaction/attraction still worked or were prevalent. And it turns out that, in general, the online world is the world today.

Meeting your partner in primary/secondary school has clearly gone out of fashion since the 40s.
Meeting your partner in primary/secondary school has clearly gone out of fashion since the 40s.

My problem with the graphic is that it is a bit too spaghettified for my liking. Too many lines, too many colours, and they are all overlapping. I probably would have tried a few different tricks. One, small multiples. The drawback to that method is that while it allows you to clearly analyse one particular series, you lose the overlap that might be of some interest to readers.

Second, maybe don’t highlight every single channel? Again, you could lose some audience interest, but it would allow the reader to more clearly see the online trend, especially in the heterosexual couple section of the data. You could accomplish this by either greying out uninteresting lines or removing them entirely, like that primary/secondary school series.

Third, I would try a bit more consistent labelling. Maybe increase the overall height of the graphic to give some more vertical space to try and label each series to the right or left of the graphic. You might need a line here or there to connect the series to its label, but that is already happening in this chart.

However, I do like how the designers kept the y-axis scale the same for both charts. It allows you to clearly see how much of an impact the online dating world has been for homosexual couples. My back-of-the-envelope calculations would say that is more than three times as successful than it is for heterosexual couples. But that insight would be lost if both charts were plotted on separate axis scales.

But lastly, note how the dataset only goes as far as 2010. I can only imagine how these charts would look if the data continued through 2018.

Credit for the piece goes to the Economist Data Team.

Most Liveable Cities Ranking

There is nothing super sophisticated in these charts, but I love them all the same. The Economist Intelligence Unit (EIU) published its rankings of the world’s most liveable cities and this year Vienna knocked off Melbourne for top spot. But what about the rest of the list?

Thankfully the Economist, a related company, put together a graphic highlighting important or noteworthy cities among the entire dataset. It is a wonderful tangle of light grey lines that have select cities highlighted in thicker strokes and brighter colours. Labelling each city would be too tricky at this scale.

I'm okay with the occasional rainbow spaghetti

I’m okay with the occasional rainbow spaghettiThat said about labelling each city, a few years back I worked on a similar top cities in a category datagraphic for Euromonitor International. We took a similar approach and coloured lines by region, but we presented the entire dataset and then complemented it by some additional charts to the side.

These were always fun pieces on which to work
These were always fun pieces on which to work

What is really nice about the Economist piece, however, is that they opted not to show the whole dataset. This could be a business decision, if people want to find where a particular city they could be persuaded to either outright subscribe or otherwise provide contact information in exchange for access to the data. Either way, the result is a piece that has space to provide textual context about why cities rose or fell over the years.

I think I like these types of pieces because there is so much to glean from getting lost in the chart. And this one from the Economist does not disappoint.

Credit for the liveability piece goes to the Economist Data Team.

Credit for the destinations piece goes to me.

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.

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.

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.

Facebook’s Share Price Plunge

Last Thursday, Facebook’s share price plunged on the news of some not so great numbers from the company on its quarterly earnings report. The data and number itself is not terribly surprising—it is a line chart. But what I loved is how the New York Times handled this on the front of the Business section on Friday morning.

The overall page
The overall page

I found the layout of the page and that article striking. In particular, each day of the share price is almost self-contained in that the axis lines start and stop for each day. I question the thickness of the stroke as something a little thinner might have been a bit clearer on the data. However, it might also have not been strong enough to carry the attention at the top of the page. As it is, that attention is needed to draw the reader down the page and then down across the fold.

Additionally, the designers were sensitive to the need to draw that attention down the page. In order to do that they kept the white space around the graphic and kept the text to two small blocks before moving on to the interior of the section.

Credit for the story goes to Matthew Philips. Although I’m pretty sure the page layout goes to somebody else.