The minimum wage of $15 per hour does not necessarily mean the same thing to everyone all across the country. Based on where one lives, the purchasing power of a dollar might make minimum wage worth more or less than $15. The Pew Research Centre put together a map showing where $15 is worth more or less.
Credit for the piece goes to the Pew Research Centre.
The UN released some new population estimates. And no surprise here, the world is still getting larger and a lot of that growth will be in Africa. But the Economist put together a graphic looking at some of the forecasts, including the ever popular bragging rights of “Who is the Largest Country?”
Credit for the piece goes to the Economist Data Team.
In today’s post we look at a graphic made by the South China Morning Post to explain the Greek Crisis. The graphic does a nice job anchoring the story in a combined chart and timeline. The reader then continues down the piece learning about additional points from demographics to text-based explanations.
Credit for the piece goes to the South China Morning Post graphics department.
As I said yesterday, I’m up in northern Wisconsin. But sometime later today I should be starting a long drive back to Chicago. So let me continue with one more piece of genealogy- and information-related content that is especially relevant given recent events. Vox posted an article a couple of days ago that looked at the definition of black via census options. Of particular interest is the supplemental or sidebar information: whether you could choose your own race or whether it was chosen for you by the enumerator.
Maybe it’s only a coincidence that the 1890 census records went up in flames.
Credit for the piece goes to the Vox graphics department.
I’m presently off in the northern reaches of Wisconsin, Ashland in particular, researching part of my family’s history. To aid me in understanding just how this frontier-following family moved over one century, I put together a crude map and a timeline to give me context (and jog my memory) while searching through files in the courthouse.
I am calling the map a migration map. It shows the locations where family members moved to in 1849: Sheboygan (from New Brunswick, Canada). And then how they quickly began to disperse, but slowly head north to Ashland County, before most ultimately headed to the West Coast. (My direct ancestors are that group near the bottom that move back to the in-laws original home of western Massachusetts.)
What I struggle with keeping in mind is that here we are looking at a perfectly rendered and understood map of modern Wisconsin. But in 1849, the state was but one year old and most of the towns to which this family would be going were only a decade or so old and still very much frontier towns without amenities. (Which is why I imagine the women of the family stayed in Milwaukee until the settlements in the north were, well, settled.)
To the right is a timeline. The details are not terribly important and in fact it is poorly designed. But, it was quick to make and will hopefully help me keep the names straight and the places for which I am looking top-of-mind.
Put the two together and you have an example of how I create visualisations for myself just to help me with my own work and research.
Well, thanks to a reddit editor frayuk, via a nice post on Vox, we now can look at what that world would look like. It’s a bit difficult to see some of the details, but click through to the Vox piece to see just those.
Today’s post looks at an infographic from the South China Morning Post. The graphic in question looks at languages and how many speak them. Specifically, the graphic narrows the focus down to those native languages spoken by 50+ million people, of which there are 23 spoken by a combined 4.1 billion people out of the world’s 7.2 billion inhabitants.
Last week we looked at the New York Times piece on where you grew up’s impact on future income. This week, we look at their follow-on piece, how your hometown impacts your odds of getting married. The piece includes some nice interactive choropleth maps, but my favourite part is the scatter plot correlating politics (as determined by 2012 election votes) to marriage. My hometown (‘s county) is highlighted in the screenshot below.
Credit for the piece goes to David Leonhardt and Kevin Quealy.
Monday was Memorial Day here in the States. As a millennial, that means I have spent nearly most of my life in wartime. Today’s post looks at a graphic from the Washington Post that explains how anybody born after 2001 has spent the entirety of their life in wartime. Before then, however, and the numbers get fuzzier, because of the subjective nature of when the United States has been at war. But, given the undercounting in the article—as it notes—it is safe to say that the percentages visualised are low.
Credit for the piece goes to the Washington Post graphics department.
Today we have a really interesting piece from the New York Times. In terms of visualisations, we see nothing special nor revolutionary—that is not to say it is not well done. The screenshot below is from the selection of my hometown county, Chester County in Pennsylvania. Where the piece really shines is when you begin looking at different counties. The text of the article appears to be tailored to fit different counties. But with so many counties in the country, clearly it is being done programmatically. You can begin to see where it falls apart when you select rather remote counties out west.
But it does not stop simply with location. Try using the controls in the upper right to compare genders or income quartiles. The text changes for those as well.
Credit for the piece goes to Gregor Aisch, Eric Buth, Matthew Bloch, Amanda Cox, and Kevin Quealy.