As you all probably know, Hurricane Florence crashed into the Carolinas this past weekend. And while I was on holiday, I did see a few articles about the storm and its impact. This one from the New York Times captured my attention because of its use of—surprise, surprise—maps.
In particular, as the user scrolls through the experience, he or she sees the change in population density of the region from 1990 to 2010. Spoiler, a lot more people now live near the coast.
In terms of the graphic, however, I wonder if a simpler approach could have communicated that part of the story more clearly. Could the map have simply shown the change in density instead of visually transforming from one number to the next? Or maybe a summary map could have followed those transitions?
Credit for the piece goes to Stephen M. Strader and Stuart A. Thompson.
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 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.
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.
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.
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.
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.
The weather in Philly the past week has been just gross. It reminds of Florida in that it has been hot, steamy, storms and downpours pop up out of nowhere then disappear, and just, generally, gross. I do not understand how people live in Florida year round. Anyway, that got me thinking about this piece from a month ago in the New York Times. It looked at the impact of climate change and living conditions in South Asia. Why is South Asia important? Well, it is home to nearly a billion people, a large number of whom are poor and demanding resources, and oh yeah, has a few countries that have fought several wars against each other and are armed with nuclear weapons. South Asia is important.
The map from the piece—it also features a nice set of small multiples of rising temperatures in six countries—shows starkly how moderate emissions and the high projection of emissions will impact the region. Spoiler: not well. It notes how cities like Karachi, for example, will be impacted as hotter temperatures mean lower labour productivity means worse public health means lower standard of living. And it doesn’t take a rocket scientist to see how things like demand for water in desert or arid areas could spark a conflict between Pakistan and India. Although, to be very clear, the article does not go there.
As to the design of the graphic, I wonder about the use of white for no impact and grey for no data. Should they have been reversed? As it is, the use of white for no impact makes the regions of impact, most notably central India, stand out all the more clearly. But it then also highlights the regions of no data.
Credit for the piece goes to Somini Sengupta and Nadja Popovich.
Everybody loves maps. Unfortunately this is not a map to love. The Economist looked at the global status of the free press and its decline around the world.
The graphic is a neat little package of a map to anchor the narrative and a few callout countries with their general declines—or in Tunisia’s case the reversal thereof—highlighted. But I do have a few issues with the piece.
Do the lines need to be curved? Some certainly make sense, e.g. how do you get from the Turkey box to the outline of Turkey? But then for Afghanistan, a straight line through Balochistan, Pakistan would mean the line would not have to cover Pakistan, India, curve around Sri Lanka, and then finally reach the box.
In the little boxes, I also wonder if the lines need to be as thick as they are. Could a lighter stroke weight improve the legibility of the charts?
And to be super picky, I wonder if the stroke outlines of the countries are complete. My trained eye fails to register an outline of both the European part of Turkey and of the Russian oblast of Kaliningrad.
Credit for the piece goes to the Economist’s Data Team.
A few months ago I covered an editorial piece from the New York Times that looked at all the action, by which I mean inaction, the federal government had taken on gun violence in the wake of some horrific shootings. Well on Saturday the Washington Post published an article looking at how there has been action on the state level.
It used a series of small multiple maps of the United States with states represented as tiles or boxes. States are coloured by whether they took action in one of six different categories. It is a pretty simple and straightforward design that works well.
The only thing I am unsure about is whether the colours are necessary. A single colour could be used effectively given that each map has a clear title directly above it. Now, if the dataset were to be used in another chart or graphic alongside the maps where the types of action were combined, then colours could be justified. For example, if there was a way to see what actions a state had taken, i.e. pivot the data display, the different colours could show what from the set the state had done.
And in Pennsylvania’s case, sadly, that is nothing.
The other day somebody mentioned to me that Africa is big, to which I agreed. It is big. It contains, depending upon how you count, about 55 countries and over one billion people. It stretches from Mediterranean climates and deserts in the north to rainforests around the equator and then back down through steppe climates to the southern coast of South Africa.
But in that vast territory also comes jihadist violence, and in this article by the Economist, it points out that despite that vastness, the violence can be found in two main areas: first, along the Mediterranean coast and, second, along the Sahel and savannah.
The map uses dots to nice effect here, pinpointing the actual locations of violence and then providing additional detail by colouring the dots according to the perpetrators of the violence. But what I really enjoyed was the simple effect of tying together the dot colours to the stacked area chart in the lower left. It shows the number of people killer per year. And while significantly up from 2010, at least the number of people killed by Boko Haram is down from its heights in 2014–15.
But the reason I brought up the vastness at the beginning is that while these are all groups following a jihadist ideology, many are also driven by very local concerns. Consequently they likely have local solutions. And we need to be careful about how much lumping together we do about jihadist violence in Africa.
Credit for the piece goes to the Economist data team.
The United Kingdom has been…well, enjoying is not the right word for me, so let’s just say witnessing a heatwave. And it is having some unexpected consequences. In short, things like grass will behave differently in extreme conditions when planted on soil vs. when growing atop stone, wood, or other non-natural features. This helps identify foundations and alike for long-forgotten structures. The BBC has a nice piece looking at some work just like this discovered across the British Isles.
Credit for the piece goes to Paul Hancock and PH Aerial Photograph.
For much of the last two weeks the world has followed the drama unfolding in Thailand, where a youth football team has been trapped underground in a partially flooded cave complex. This weekend, rescuers, who had overcome a daunting challenge of simply finding them, began extracting the boys. And this graphic from the BBC shows just how challenging their extraction will be.
In particular I like this map. It illustrates both the path of the cave, but also shows how uneven the interior structure is. It does that by showing select cross sections with a person to scale. Some parts are so small and narrow that people can barely squeeze through.
Credit for the piece goes to the BBC graphics department.