So I finally got my blink(1) from ThingM! I will call the blink(1) product a small-scale indicator. Small-scale sensors have been proliferating in recent years. The smartphone is the most obvious. Another revolution I see coming is in the small-scale indicators. Blink(1) is one such device. Since I love Processing and anything nerdy, I have written a Processing Sketch to show some of the abilities of blink(1). The Mouse’s X and Y position determine color. The blinking is based on the speed of the movement. After a certain pixel distance threshold the color is set to 0.
First you obviously need to get a blink(1) and plug it in!
Headcharts, (or facegraphs) are like headshots for data. Well, no not really, it just sounds like a catchy opening sentence. Anyways I was playing with Processing awhile ago and I did a basic tutorial and got processing to find my face and draw a rectangle on it. I used a library called openCV (Open Computer Vision). It worked well and it was a fun activity to try. (This website has more information on getting openCV into Processing: http://ubaa.net/shared/processing/opencv/ )
This week I decided to re-visit the software and I was able to get a simple chart to follow my face. Imagine if every morning your intelligent mirror showed you what you ate yesterday and your exercise levels.
Lets say you’re against taxes and spending. Should you use a graphic that over-represents, under-represents, or accurately displays taxes and spending relative to something else? The Heritage Foundation released this graphic last week:
The problem with Pie Charts and these type Area charts is that the something 4x the size only really looks like 2x the size and so on. Assuming The Heritage group is against the taxes and spending, (as my knowledge of them and the the big red letters seem to indicate), it’s bizarre why they would choose an inferior chart to show how large difference between the two things they would like to compare. 1.6 trillion is 4x 400 billion, but in their graphic the left box is only ~330 pixels tall, while the right graphic is about half that at 163 pixels (y axis was the same). The problem is that they are taking one dimensional data and distributing it across two dimensions! There’s no need for it when a simple bar chart would get the point across better. For instance, here is a comparison of what that 2d volume chart would look like vs a similar bar chart:
Which graphic clearly shows “one thing is 4 times another”? IT JUST MAKES NO SENSE! Why undermine your position by inaccurately under-representing your cause!? This is why the left is ‘winning’, they’re not shooting themselves in the foot with terrible understanding of graphics and data representation.
So today I got an email from my state senator in GA, Chip Rogers. This issue at present is whether the GA constitution should be amended to allow to multi-year rentals by the state of GA. The idea behind the state can save money by entering into multi-year rentals at lower rates. The state Majority Leader, who is in favor of it, claims it will save $66 million over 10 years. A counter-argument can found here.
My issue is this piece of terrible mathematics by my state senator Chip Rogers:
“A conservative estimate prepared by the State Properties Commission estimates over $66 million in savings will result over ten years, with the potential of even more future savings. $66 million could pay the average salaries for over 1,300 teachers or police officers in Georgia.” …Yeah if we ignore the math by a factor of 10.
The problem with this and other ‘savings’ purported by our government officials is this ‘over 10 years’ crap. It is a ploy to inflate their numbers and make mathematical deception much easier. In reality the plan would only annually save 130 jobs IN THE ENTIRE STATE OF GA, which for you out-of-staters, has a population of ~9.8 million. Basically they have to multiply their achievement by 10 because they’re not doing jack squat to help us.
$66,000,000 over 10 years = $6,600,000 average per year savings. $6,600,000 / 130 jobs is ~$50 k a year.
I have a hard time believing this is an ‘honest mistake’. I mean we are in freaking 2012. If you had a question about the whole thing, just type the crap directly into Wolfrum Mathematica and see what it says! Wrong: Right:
Also, this amount is truly trivial in the entire scope of things:
$19,300,000,000 – 2012 State Budget
$6,600,000 – Average 1 year savings
0.03% Of Budget saved!
Politicians, please don’t make me barf and insult my intelligence. This small of a savings shouldn’t be touted as a great savings for the people and insist we vote for it. It’s absurd. Hey look at me! I saved .03% of the budget over 1 year… that’s .3% over 10 years! Or 3% over 100 years! What is really happening is this is a give-away to the politically connected. Their friends will likely get nice sweet deals, probably multi-year leases with big penalties for early cancelation. THIS IS CRONY CAPITALISM! I voted no on the amendment by the way, if it were 2 or 3 years I would have voted yes regardless of the terrible political math. Frankly vote no so we can “limit the amount of money that can be stolen from taxpayers at one sitting.” to quote Charlie from PeachPundit.
This was made by and in-law of mine, Charles C., and I thought it was a great chart showing the trends in employment. I have zoomed in on the last two presidents. The funny codes are actually BLS numbers so you can get the data yourself and make your own charts. For instance here is the data for LNS12300061
Here is a quick chart showing the value of a home game for soccer (aka football). I took the Manchester City football (aka soccer in the US, but I will call it football or association football from here on out) data and aggregated it by team and make this cool chart showing the differences between home and away games. Home games have more goals and assists, less goals conceded and penalties. Clearly the fans have an impact on the games.
Manchester City Football Club offered up a great selection of soccer data. I have been crunching it with my free time and it is pretty cool. God bless open data. There are hundreds of columns, but I have only looked at a few pieces of obvious data, such as the relationship between shots and goals, which should be obvious for any soccer fan.
Same graph broken up by position. (Note the different Y axis)
In case you missed it and are interested in Sports Analytics, Manchester City Football Club is releasing their data to the public. You must sign up for it and wait a few days (scroll to the bottom of the main analytics page for the sign-up). I got the data late last week and I looked over a few things and was quite impressed. First of all, the ‘lite’ data is 10k+ rows and 200+ columns. To me that is quite a large sample that we can probably gather some real confidence in.
I have been very busy making dashboards for work. I am currently using Microsoft Performance Point, and it leaves much to be desired in the formatting area. Since I am not a graphic designer, nor a web developer, I am a bit hamstrung when it comes to delivering the ‘last mile’ ah-ha moment in SharePoint. Believe me, what we have now using SharePoint is a million times better than having no visibility. I have several good looking reports, but there are just a few tweaks I would like to do. Anyways I was recently exploring Juice Analytics’ Slice product and since their Atlanta offices are right near mine I was able to visit their office and they nicely gave me the ability to demo their software. I have used some soccer data that I collected with @gregesque and made a fun dashboard located here (this dashboard displays quite nicely in a vertical portrait format so this might blow your minds, but pic your monitor up and turn it on end and change the settings to portrait mode).
It brings me up to another subject. What is the best layout is best for a dashboard? Square, portrait, landscape? I really enjoyed working with my slice dashboard on a portrait mode 1050×1680. Obviously I can’t require my users to change their screens to portrait mode to view my dashboards, but for any public interactive dashboards, portrait mode seems awesome.
(Note that this tree map is built off of selected players and doesn’t encompass all the goals scored that season)
Last week the released their Facebook IPO, which was by far the biggest IPO in history and the New York Times does a fantastic job of providing an interactive graphic of US IPOs. Page 2 shows, in a very effective manner, how abnormal the IPO was:
Now the scale here was chosen to show the unique character of Facebook’s IPO, but the chart on the next page show the same information with a log-scale. I have also added some annotations to that chart.
In the type of data I typically have contact with, (business data) I usually look at things in both a normal scale and a log-scale because the natural distribution of many things follows the Pareto Principle. By simply including the Log-Scale as one of the options the NYT chart, they have correctly enabled the users to accurately view massive and small things very easily. This Log-Scale chart (on page 3) really jumped out at me and made me ask a question: “Why are small IPOs virtually non-existent after 2001?” Before 2001 there was a forest of small little dots on this chart except during the recessions.
Going through school around that time I was probably much more politically astute than my age would indicate (and taking two accounting classes soon afterwards really helped) I learned about about the Sarbanes–Oxley Act and immediately saw it’s effect after looking at the chart.
Everyone knows that regulations cost ‘something.’ Even if it only costs time to comply with regulations then that time which was not spent doing something else. These costs may be offset of course by greater social benefits and the public good, but what is the net effect of a regulation on people’s behavior? Likely that increase in costs affects those least able to pay it, which are smaller businesses or poorer people. One knee-jerk law affecting business was the Sarbanes–Oxley Act of 2002. There has been another recent knee-jerk law (both signed by the ‘business friendly’ Bush), the Consumer Product Safety Improvement Act of 2008. This law required required lead testing on all kid items, even if they never had a lead problem before (children’s books), or inherently never contain lead (wool). It was passed after a series of tainted product came from China, and applies to US and European-made products, even though those areas never supplied ‘leaded’ toys. Many criticisms can be found on the law.
Sadly, I fear that the data on small businesses in the toy manufacturing industry will be very hard to come by and the same chart as I have shown above will never be created.