Abortion by State

In case you did not hear, earlier this week Alabama banned all abortions. And for once, we do not have to add the usual caveat of “except in cases of rape or incest”. In Alabama, even in cases of rape and incest, women will not have the option of having an abortion.

And in Georgia, legislators are debating a bill that will not only strictly limit women’s rights to have an abortion, but will leave them, among other things, liable for criminal charges for travelling out of state to have an abortion.

Consequently, the New York Times created a piece that explores the different abortion bans on a state-by-state basis. It includes several nice graphics including what we increasingly at work called a box map. The map sits above the article and introduces the subject direct from the header that seven states have introduced significant legislation this year. The map highlights those seven states.

We've been calling these box maps. It's growing on me.
We’ve been calling these box maps. It’s growing on me.

The gem, however, is a timeline of sorts that shows when states ban abortion based on how long since a woman’s last period.

There are some crazy shifts leftward in this graphic…
There are some crazy shifts leftward in this graphic…

It does a nice job of segmenting the number of weeks into not trimesters and highlighting the first, which traditionally had been the lower limit for conservative states. It also uses a nice yellow overlay to indicate the traditional limits determined by the Roe v. Wade decision. I may have introduced a nice thin rule to even further segment the first trimester into the first six week period.

We also have a nice calendar-like small multiple series showing states that have introduced but not passed, passed but vetoed, passed, and pending legislation with the intention of completely banning abortion and also completely banning it after six weeks.

Far too many boxes on the right…
Far too many boxes on the right…

This does a nice job of using the coloured boxes to show the states have passed legislation. However, the grey coloured boxes seem a bit disingenuous in that they still represent a topically significant number: states that have introduced legislation. It almost seems as if the grey should be all 50 states, like in the box map, and that these states should be in some different colour. Because the eight or 15 in the 2019 column are a small percentage of all 50 states, but they could—and likely will—have an oversized impact on women’s rights in the year to come.

That said, it is a solid graphic overall. And taken together the piece overall does a nice job of showing just how restrictive these new pieces of legislation truly are. And how geographically limited in scope they are. Notably, some states people might not associate with seemingly draconian laws are found in surprising places: Pennsylvania, Illinois, Maryland, and New York. But that last point would be best illustrated by another box map.

Credit for the piece goes to K.K. Rebecca Lai.

Pennsylvania’s Population Shifts

Last month the US Census Bureau published their first batch of 2018 population estimates for states and counties. Pennsylvania is one of those states that is growing, but rather slowly. It will likely lose out to southern and western states in the 2020 census after which House seats will be reapportioned and electoral college votes subtracted.

From 2018 to 2010, the Commonwealth has grown 0.8%. Like I said, not a whole lot. But unlike some states (Illinois), it is at least growing. But Pennsylvania is a very diverse state. It has very rural agricultural communities and then also one of the densest and largest cities in the entire country with the whole lot in between . Where is the growth happening—or not—throughout the state? Fortunately we have county-level data to look at and here we go.

Some definite geographic patterns here…
Some definite geographic patterns here…

The most immediate takeaway is that the bulk of the growth is clearly happening in the southeastern part of the state, that is, broadly along the Keystone Corridor, the Amtrak line linking Harrisburg and Philadelphia. It’s also happening up north of Philadelphia into the exurbs and satellite cities.

We see two growth outliers. The one in the centre of the state is Centre County, home to the main campus of Pennsylvania State University. And then we have Butler County in the west, just north of Pittsburgh.

The lightest of reds are the lowest declines, in percentage terms. And those seem to be clustered around Scranton and Pittsburgh, along with the counties surrounding Centre County.

Everywhere else in the state is shrinking and by not insignificant amounts. Of course this data does not say where people are moving to from these counties. Nor does it say why. But come 2020, if the pattern holds, the state will need to take a look at its future planning. (Regional transit spending, I’m looking at you.)

Natural Disasters

Today’s piece is another piece set against a black background. Today we look at one on natural disasters, created by both weather and geography/geology alike.

The Washington Post mapped a number of different disaster types: flooding, temperature, fire, lightning, earthquakes, &c. and plotted them geographically. Pretty clear patterns emerge pretty quickly. I was torn between which screenshots to share, but ultimately I decided on this one of temperature. (The earthquake and volcano graphic was a very near second.)

Pretty clear where I'd prefer to be…
Pretty clear where I’d prefer to be…

It isn’t complicated. Colder temperatures are in a cool blue and warmer temperatures in a warm red. The brighter the respective colour, the more intense the extreme temperatures. As you all know, I am averse to warm weather and so I will naturally default to living somewhere in the upper Midwest or maybe Maine. It is pretty clear that I will not really countenance moving to the desert southwest or Texas. But places such as Philadelphia, New York, and Washington are squarely in the blacked out or at least very dark grey range of, not super bad.

Credit for the piece goes to Tim Meko.

Trump-won Counties Are Winning

Yesterday we looked at how China and the European Union are planning their tariff/trade war retaliation to target Trump voters. Today let’s take a look at how those voters are doing as this article from Bloom does.

Lots of green, but some noticeably red counties in Florida.
Lots of green, but some noticeably red counties in Florida.

The article is not terribly complicated. We have four choropleth maps at the county level. Two of the maps isolate Trump-won counties and the other two are Clinton-won. For each candidate we have a GDP growth and an employment growth map.

In the Trump-won maps, the Clinton-won counties are white, and vice versa. Naturally, because the Democratic vote is greatest in the large cities, which, especially on the East Coast, are in tiny counties, you see a lot less colour in the Clinton maps.

Not a whole lot to see here…
Not a whole lot to see here…

Design wise, I should point out the obvious that green-to-red maps are not usually ideal. But the designers did a nice job of tweaking these specific colours so that when tested, these burnt oranges and green-blues do provide contrast.

Here they appear more of a yellow to grey
Here they appear more of a yellow to grey

But I am really curious to see this data plotted out in a scatter plot. Of course the big counties in the desert southwest are noticeable. But what about Philadelphia County? Cook County? Kings County? A scatter plot would make them equally tiny dots. Well, hopefully not tiny. But then when you compare GDP growth and employment growth and benchmark them against the US average, we might see some interesting patterns emerge that are otherwise masked behind the hugeness of western counties.

But lastly. And always. Where. Are .Alaska. And. Hawaii? (Of course the hugeness problem is of a different scale in Hawaii. Their county equivalents are larger than states combined.)

Credit for the piece goes to the Bloomberg graphics department.

Trade War Retaliation

About a week and a half ago the Economist published an article about the retaliatory actions of the European Union and China against the tariffs imposed by the Trump administration. Of course last week we had a theme of sorts with lineages and ancestry. So this week, back to the fun stuff.

What makes today’s piece particularly relevant is that over the weekend, Trump announced he might increase the tariffs proposed, but not yet implemented, upon Chinese goods. So some economists looked at the retaliatory tariffs proposed by the EU and China.

Ultimately Trump's tariffs are not paid by foreign governments, but by US citizens.
Ultimately Trump’s tariffs are not paid by foreign governments, but by US citizens.

Each targets Trump voters, albeit of different types. But China appears more willing to engage in a brutal fight. Its tariff proposal would not just harm Trump voters, but would also harm Chinese citizens. The EU’s plan appears tailored to maximise the pain on Trump voters, but minimise that felt by its own citizens.

A few minor points. I like how the designers chose to highlight high impact categories with colour. Lower impact shares are two shades of light grey. But after that, the scale changes. I wonder how the maps would compare if each had been set to the same scale. It looks doable as the bottom range of the maximum bin is 6% for the EU and 8% for China. (Their high limit is much higher at 22% compared to the EU’s 10%.)

That said, it does a good job of showing the different geographic footprints of the two retaliatory tariff packages. Tomorrow—barring breaking news—we will look at why that is important.

Credit for the piece goes to the Economist Data Team.

The Great Migration Map

Yesterday in a post about Angela’s forced journey from Africa to Jamestown I mentioned that the Pilgrims arrived at Plymouth Bay just one year later in 1620. From 1620 until 1640 approximately 20,000 people left England and other centres like Leiden in the Netherlands for New England. Unlike places like Jamestown that were founded primarily for economic reasons, New England was settled for religious reasons. Consequently, whereas colonies in Virginia drew young men looking to make it rich—along with slaves to help them—New England saw entire families moving and transplanting parts of towns and England into Massachusetts, Rhode Island, Connecticut, and New Hampshire.

New England kept fantastic records and we know thousands of people. But we do not know whence everyone arrived, but we do know a few thousand. And this mapping project from American Ancestors attempts to capture that information at the English parish level. At its broadest level it is a county-level choropleth that shows, for those for whom we have the information, the majority of the migration, called the Great Migration, came from eastern England, with a few from the southwest.

Quite a few from Norfolk, Suffolk, and Essex
Quite a few from Norfolk, Suffolk, and Essex

You can also search for specific people, in which case it brings into focus the county and the parishes within that have more detail. In this case I searched for my ancestor Matthew Allyn, who was one of the founders of Hartford, Connecticut. He came from Braunton in Devon and consequently appears as one of the two people connected to that parish.

Devon did not have nearly as many people emigrate as the eastern counties
Devon did not have nearly as many people emigrate as the eastern counties
But was Thomas related to Matthew? We don't know.
But was Thomas related to Matthew? We don’t know.

Overall, it’s a nice way of combining data visualisation and my interest/hobby of genealogy. The map uses the historical boundaries of parishes prior to 1851, which is important given how boundaries are likely to change over the centuries.

This will be a nice tool for those interested in genealogy and that have ancestors that can be traced back to England. I might be biased, but I really like it.

Credit for the piece goes to Robert Charles Anderson, Giovanni Flammia, Peter H. Van Demark.

Angela from Jamestown

Today we move from royalty to slavery. Earlier this week the Washington Post published an article about an African woman (girl?) named Angela. She was forcibly removed from West Africa to Luanda in present-day Angola. From there she was crammed into a slave ship and sent towards Spanish colonies in the Caribbean. Before she arrived, however, her ship was intercepted by English pirates that took her and several others as their spoils to sell to English colonists.

The article is a fascinating read and for our purposes it makes use of two graphics. The one is a bar chart plotting the Atlantic slave trade. It makes use of annotations to provide a rich context for the peaks and valleys—importantly it includes not just the British colonies, but Spanish and Portuguese as well.

My favourite, however, is the Sankey diagram that shows the trade in 1619 specifically, i.e. the year Angela was transported across the Atlantic.

Too many people took similar routes to the New World.
Too many people took similar routes to the New World.

It takes the total number of people leaving Luanda and then breaks those flows into different paths based on their geographic destinations. The width of those lines or flows represents the volume, in this case people being sold into slavery. That Angela made it to Jamestown is surprising. After all, most of her peers were being sent to Vera Cruz.

But the year 1619 is important. Because 2019 marks the 400th anniversary of the first slaves being brought into Jamestown and the Virginia colony. The Pilgrims that found Plymouth Bay Colony will not land on Cape Cod until 1620, a year later. The enslavement of people like Angela was built into the foundation of the American colonies.

The article points out how work is being done to try and find Angela’s remains. If that happens, researchers can learn much more about her. And that leads one researcher to make this powerful statement.

We will know more about this person, and we can reclaim her humanity.

For the record, I don’t necessarily love the textured background in the graphics. But I understand the aesthetic direction the designers chose and it does make sense. I do like, however, how they do not overly distract from the underlying data and the narrative they present.

Credit for the piece goes to Lauren Tierney and Armand Emamdjomeh.

American Nuclear Generating Stations

Those that have followed me for a long time know that I am a big fan of nuclear power. It does have some drawbacks, namely its radioactive waste, but otherwise creates enormous amounts of stable, carbon-free electricity. So when I saw this article from Bloomberg about the impact of climate change on US nuclear powered electricity generating station. It makes use of a number of nice maps to show that, yeah, not good things.

Pennsylvania is a big state for nuclear power
Pennsylvania is a big state for nuclear power

I normally am not a huge fan of scaling circle size to the data point, but here it makes sense since the circles are tied to the geographical location. Like I mentioned with the one Notre Dame graphic, I’m not sure the advantage of the black background, but it could be that there is a benefit to the contrast over the white background.

There are additional maps in the piece that look at a few specific locations in a moderate hurricane and the expected storm surge. Again, not good. These also use light colours on a dark background.

Credit for the piece goes to Christopher Flavelle and Jeremy C.F. Lin.

Carbon Taxes

Last week the New York Times published an article about carbon taxes, looking at their adoption around the world and their effectiveness. It is a fascinating article about how different countries have chosen to implement the broad policy idea and the various forms it can take. And, most importantly, how some of those policies can end up blunting the intended effect of carbon emission reduction.

This, however, is about the print piece, because as I was flipping through the morning paper, I found the Business section had a world map above the fold. And we all know how I feel about big, splashy print graphics.

We could use some more green on this map
We could use some more green on this map

Here we have a pretty straight-forward piece. It uses a map to indicate which countries have adopted or are scheduled to adopt a carbon tax programme. The always interesting bit is how the federal system in the United States is represented. Whilst a carbon cap-and-trade deal failed in the US Senate in 2009, individual states have taken up the banner and begun to implement their own plans. Hence, the map shows the states in yellow.

There is nothing too crazy going on in the piece, but it is just a reminder that sometimes, as a designer, I love big splashy graphics to anchor an article.

Credit for the piece goes to Brad Plumer.

The Entire United States Pt 2

Yesterday I wrote about the failure in a Politico piece to include Alaska and Hawaii in a graphic depicting the “entire” United States. After I had posted it, I recalled an article I read in the Guardian that looked at the shape of the United States, using the term “logo map”. It compared what many would consider the logo map to the actual map of the United States.

Still no New Zealand…
Still no New Zealand…

I warn you, it is a long read. But it was worth it to try and reframe the idea of what does the United States look like?

Credit for the piece goes to the Guardian graphics department.