Our World In Data put together 5 charts which show how global living conditions have changed over the last two centuries. The topics include poverty, literacy, health, freedom, fertility, and education.
Archive for the 'Areas (Subject)' Category
Page 2 of 99
The Census Bureau just released its 2016 Population Estimates. Let’s take a peek at what the Electoral College might look like in 2020 using the PSC Apportionment calculator. The easiest calculation is to just put the 2016 estimates into the calculator (remember to delete Washington, DC). In that scenario:
The losers: Illinois, Michigan, Minnesota and Pennsylvania
The winners: Florida, North Carolina, Oregon, and Texas
If we take the 2010 to 2016 growth rate and extend it to 2020, this is the scenario:
Losers: Alabama, Illinois, Michigan, Minnesota, New York, Ohio, Pennsylvania, Rhode Island, West Virginia
Winners: Arizona, Colorado, Florida (2), North Carolina, Oregon, Texas (3)
Notable in this scenario is Rhode Island losing an electoral seat. It is just slightly larger than Montana – 1,056,426 vs 1,042,520. But, Rhode Island has had an extra seat since 1990 when Montana lost 1 seat in the House of Representatives. Montana is on the cusp of getting that 2nd representative in the House – it just needs ~5,000 more people than our 2020 projection, which is not an unrealistic scenario.
One thing that is unrealistic about the previous scenario is the fast growth of North Dakota during this period. North Dakota has been the fastest growing state for the past 4 years, but its growth rate dropped to 37th fastest in 2016 due to the collapse of oil prices and thus the fracking industry. Thus, a more realistic estimate might be to use the 2015-2016 rate for the last 4 years of the decade. In that scenario, the results are exactly the same, except that now Montana needs only 550 more people to gain a 2nd seat in the House of Representatives.
Vintage Population Estimates (2016)
State Population Estimates (2016)
PSC Apportionment Calculator
Representations apportioned to each state (1790 to 2010)
Congressional Apportionment Resource
Two researchers have created a map of megaregions in the US based on commuting data from the American Community Survey (ACS). The results are covered in both the popular press and in PLOS One. The latter provides more details about how they constructed the maps – it wasn’t just via a mapping program.
How 4 Million Commutes Shape America’s ‘Megaregions’
Laura Bliss | Atlantic: City Lab
December 7, 2016
An Economic Geography of the United States: From Commutes to Megaregions
Garrett Nelson and Alisdair Rae
November 30, 2016
If you are so inclined the authors have made their data available for replication via Figshare.
This is from the blogger @undercoverhistorian. We had a previous post on the site she maintains. Below is an interesting set of almost 50 tweets – some illustrated – where she defends 1952 as the most important year.
How to better communicate election forecasts — in one simple chart
Justin Gross | Monkey Cage blog [Washington Post]
November 29, 2016
Most folks were surprised by the results of the 2016 Presidential election and this was in part due to some of the rosy forecasts by some of the poll aggregators, like Huffington Post. But, even when a site had a forecast with a 30% chance of Trump winning, most people have trouble understanding that a Trump victory was possible. The explanation:
But certain representations of probability are more readily grasped than others. In particular, we have trouble understanding risk in terms of the “percent chance” but we do better when simple raw numbers of different outcomes are depicted visually.
Solution: Show the risk as a “Risk Visualization Theater.” Below are the representations of forecasts of victory for Trump via FiveThirtyEight, NYT Upshot, and Huffington Post Pollster. The filled theater seats (in black) represent the chance of a Trump victory. Clearly, the chance of that event happening don’t look so remote in the far left depiction, but look very unlikely as one moves to the right.
China has had a highly unbalanced sex ratio at birth for years leading to an estimate of 30 to 60 million missing girls. The traditional explanation was male preference, exacerbated by the one-child policy, which led to sex selective abortion and/or infanticide. New research presents evidence that maybe the missing girls were never missing after all.
Researchers may have ‘found’ many of China’s 30 million missing girls
Simon Denyer | Washington Post
November 30, 2016
Delayed Registration and Identifying the “Missing Girls” in China
Yaojiang Shi and John James Kennedy | China Daily
November 15, 2016
Ben Casselman writes in FiveThirtyEight about the ways immigrants help to keep the U.S. population young and keeps the labor force participation at a relatively high rate: Immigrants Are Keeping America Young — And the Economy Growing
A 2-hour workshop on mapping data from Detroit is offered on Thursday, November 3rd on campus. Perhaps as useful is meeting the presenter who is the founder of Detroitography.com a group that is all about maps and geography of Detroit. And, that also means geographically-referenced data.
Using the TravelTime Search API to Generate an Isochrone
GIS Lounge | GIS contributor
July 9, 2016
Using the TravelTime platform and some simple code, researchers can map how far people can travel in 30 minutes by public transportation from a specific address. This is more realistic than radius circles because these don’t take into account roads, bus routes, etc.
The TravelTime platform includes several countries, including US coasts.
These monthly webinars out of the North Carolina Library Association provide a good introduction introduction to all sorts of data products by subject experts: APIs, mapping, UN data, global trade, court records, etc. Folks can sign up and watch the presentation in real time or as a recording. Slides are available for all presentations.