Writing

Just when you thought the world revolved around you

Eugene Kuo sends a link to the Wikipedia article on center of population, an awkward term for the middlin’ place of all the people in a region. Calculation can be tricky because the Earth is round (what!?) and the statistical hooey that goes into determining a proper distance metric. The article includes a heat map of world population:

center of population

From a cited article, Wikipedia notes that:

…the world’s center of population is found to lie “at the crossroads between China, India, Pakistan and Tajikistan”, with an average distance of 5,200 kilometers (3,200 mi) to all humans…

Though sadly, the map also uses a strange color scale for the heat map, with blue the area of greatest density, and red (traditionally the “important” end of the scale) as the least populated area. Even shifting the colors helps a bit, at least in terms of highlighting the correct area:

worldcenterofpopulation_500px_hueshift.jpg

Though the shift is of questionable accuracy, and the bright green still draws too much attention, as does the banding in the middle of the Atlantic.

Outside of musing for your own edification, practical applications of calculating a population’s center include:

…locating possible sites for forward capitals, such as Brasilia, Astana or Austin. Practical selection of a new site for a capital is a complex problem that depends also on population density patterns and transportation networks.

Check the article for more about centers of various countries, including the United States:

The mean center of United States population has been calculated for each U.S. Census since 1790. If the United States map were perfectly balanced on a point, this point would be its physical centroid. Currently this point is located in Phelps County, Missouri, in the east-central part of the state. However, when Washington, D.C. was chosen as the federal capital of the United States in 1790, the center of the U.S. population was in Kent County, Maryland, a mere 47 miles (76 km) east-northeast of the new capital. Over the last two centuries, the mean center of United States population has progressed westward and, since 1930, southwesterly, reflecting population drift.

For added fun, I’ve created an interactive version of the map, based on a Processing example. (Though it took me longer to write the credits for the adaptation than to actually assemble it — thanks for all those who contributed little bits to it.)

globe_500.jpg

Monday, January 26, 2009 | mapping, population  
Book

Visualizing Data Book CoverVisualizing Data is my book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.

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