I never thought a data visualization application would point me to my next read but Amaztype actually did.

I am unsure whether the application is really data visualization or just turning “data-into-images-and-then-back-into-data-just-’coz” but I liked it and thought I would share it. Like art, data visualization may not necessarily have to have a point.

In this article, Steve Murdock, Texas demographer, defended the right to cheaper higher education to immigrants. Regardless of the obvious political implications of this choice, wouldn’t you say that it is to everyone’s advantage to secure education for all? An excerpt of that article I believe paints the picture is:

An educated work force raises income levels, which generates businesses activity and increases the market for goods and services,” Murdock said. “It also increases investments for new businesses, which in turn increases tax revenues. Higher education equals higher incomes.

It is the small, value-add, tasks that each worker provides on a day-to-day basis that make all the difference for a company at the end of the year. And it is, in my humble opinion, in the hands of education to give workers the capability to invent and put value-add tasks into practice.

Education, like food, shelter and medical services would be considered by most a human right more than a priviledge. History is plagued with the disastrous consequences of restrictions to education. Noone, regardless of how rich/educated/sheltered they are, can realistically believe to ever be safe from the implications of uneducated masses.

I hope, as many of us “middle-classers” do, that education will always be made available and encouraged, in some way or another, at least half as much as television and fast food.

I had a mind to do this for sometime as I thought recent events would likely replicate the “mad” volatility of the 30′s.

Using Dow Jones Industrial Open and Close price data* (rather than Highs and Lows) from 1928 to 2011, the map is the plotted volatility of weekly returns per year in Excel using conditional formatting against defined bins of standard deviation values.

The fact is that the Dow Jones Industrial (DJI) in recent years has shown high levels of volatility but not the same, sustained, drastic “price jumps” it endured in the 1930’s. Likewise, looking at this logarithmic plot of the DJIA, the sharpest and most recurrent “dents” (peaks and troughs) per year, are still those of the 30’s: http://en.wikipedia.org/wiki/File:DJIA_historical_graph_to_jan09_(log).svg

Not to say that current years haven’t been a nightmare for investment banking but the DJI has seen worse times… Hopefully decisions will prop up soon that will address and stabilise US and EU debt and reinstate some market confidence before a 30’s-like rollercoaster.

Some notes from the ^DJI Volatility Heat Map:
• Each column representing a year and each row representing the weeks of the year from 1 to 52 (calculating but not plotting leap year weeks), volatility tends to be higher during the second half of the year.
• The 30’s was cumulatively more volatile than the 40’s, 50’s, 60’s and 70’s put together.
• Volatility clustering shows best either side of extreme volatility figures (red cells).

The companies comprised in the DJIA (Wikipedia):
3M DuPont McDonald’s
Alcoa ExxonMobil Merck
American Express General Electric Microsoft
AT&T Hewlett-Packard Pfizer
Bank of America The Home Depot Procter & Gamble
Boeing Intel Travelers
Caterpillar IBM United Technologies Corp.
Chevron Corporation Johnson & Johnson Verizon Communications
Cisco Systems JPMorgan Chase Wal-Mart
Coca-Cola Kraft Foods Walt Disney

* Data from Yahoo! Finance. Weekly, ^DJI price data in USD from 1928 to 2011 (September).
* Feel free to post a comment for a copy of the excel sheet.

Heat Map: http://alejandraarroyo.files.wordpress.com/2011/09/volatilityheatmap_.png

Here are some links to some interesting public-level explanations of Solar Cycles, magnetic storms and sun spots. There is also some interesting data if you wish to pass the time plotting sunspot cycles from the 18th century to date.

http://solarscience.msfc.nasa.gov/3dfields.shtml

Real time data from the Solar Influences Data Center (noth to do with fertility cycles): http://sidc.oma.be/LatestSWData/LatestSWData.php

http://www.un.org/esa/population/cpd/cpd2011/cpd44.htm

“An Eagle was chasing a hare, which was running for dear life and was at her wits’ end to know where to turn for help. Presently she espied a Beetle, and begged it to aid her. So when the Eagle came up the Beetle warned her not to touch the hare, which was under its protection. But the Eagle never noticed the Beetle because it was so small, seized the hare and ate her up. The Beetle never forgot this, and used to keep an eye on the Eagle’s nest, and whenever the Eagle laid an egg it climbed up and rolled it out of the nest and broke it. At last the Eagle got so worried over the loss of her eggs that she went up to Jupiter, who is the special protector of Eagles, and begged him to give her a safe place to nest in: so he let her lay her eggs in his lap. But the Beetle noticed this and made a ball of dirt the size of an Eagle’s egg, and flew up and deposited it in Jupiter’s lap. When Jupiter saw the dirt, he stood up to shake it out of his robe, and, forgetting about the eggs, he shook them out too, and they were broken just as before. Ever since then, they say, Eagles never lay their eggs at the season when Beetles are about.
The weak will sometimes find ways to avenge an insult, even upon the strong.”