I really enjoyed this article in The Economist on the astonishing increase in textbook prices relative to the consumer price index, so I decided to investigate some other items. Food and apparel both had interesting results, so here are the graphs! These use CPI for all urban consumers, and the data are seasonally adjusted.
I have previously defended Portland’s weather. The point I made was that, while it absolutely rains more often (more days per year) in Portland than most other large cities, we get less rain overall (in terms of depth of water). These maps visualize the latter point using average precipitation from 30-yr normals (1981-2010). Note that almost half of Portland’s precipitation occurs in November-January, but the combined precipitation in July and August is less than 4% of the annual total. To emphasize this seasonality, I’ve also mapped normals for July and December, when Portland is drier and wetter, respectively, than most of the country.
First things first – I’m not a Mormon. I loved the musical (The Book of Mormon) and Krakauer’s Under the Banner of Heaven. While I may not agree with or even understand the LDS beliefs, I’m fascinated by their propagation capabilities (both in terms of reproduction and proselytizing). The LDS Church is such a fast growing denomination, it makes me wonder why other religions don’t try to mimic their approach. It’s just impressive.
This graphic reveals the geographic spread of the LDS Church as a function of time. Its growth has been focused particularly in the past 30 years. Of the 143 currently operating temples, 123 (86%) were dedicated in 1983 or later. It should be noted that this graphic only shows temples, not churches. There are many more churches than temples!
I was reading some of the comments about the very sad story of Michael Brown’s killing in Ferguson, MO. One reader claimed that most homicides are white killing white or black killing black, rather than interracial. While this is true, it doesn’t diminish the impact of a horrible event like this.
To make this graph, I’ve taken a five-year average of homicide rates from the FBI crime reports. The numbers are raw; they are not normalized by the demographic breakdown of the US. Please be aware that these are based on race, not ethnicity! For the purpose of these data, the FBI considers Hispanic/Latino to be an ethnicity.
I recently watched several of The International 4 matches. I’d never seen Dota 2 before and, while it was entertaining, some of the games seemed to drag on a bit longer than I expected. As a mediocre SC2 player, my games are over in 15 minutes. I guess zergling rushes don’t exist in Dota 2. So I searched the forums for average game length, and was surprised by how many discussions there were with a lot of individual opinions but no consensus answer. Obviously, game length is different for average players than it is for pros, but it was easier to get game length results from premier tournaments, so that’s what I’ve used here. I added League of Legends to make the graph slightly more interesting.
For SC2, I used GSL tournaments, including Up & Down, Code A, and Code S matches.
For Dota2, I used The International (2, 3, and 4), but only Captains Mode games.
I don’t know anything about LoL, so I tried to choose tournaments that had the most prize money. That included Season 3 World Championship, PANDORA.TV Champions Winter 2013-2014, HOT6iX Champions Summer 2013, and a couple slightly smaller ones that reported game lengths.
The USA imprisons a lot of people; it has more than 700 prisoners per 100k population. As a country, its imprisonment rate is second only to Seychelles (which is a small African country comprising many islands with only 90k people). The USA has 21.7% of the global prisoner population, but only 4.4% of the total global population. So is the USA legal system too effective? Or are other countries’ systems not effective enough?
This graphic puts the issue into perspective. The area of each country’s rectangle is proportional to the total number of prisoners it has. The value for the color is normalized using each country’s population (prisoners per 100k people).
As we all know, many of the greatest distance runners come from Kenya and Ethiopia, and the world’s fastest sprinter (Usain Bolt) is Jamaican. How do the best runners from other countries compare?
These maps show fastest race time by country relative to the world record for 100 m, 1500 m, 10 km, and a marathon. The data are based on men’s records, and do not include wind-assisted times. A sample calculation is provided to show the meaning of the scale. All times were divided by the world record time, and then converted to percentage slower than world record time.
Unfortunately, despite the source having thousands of completion times for each race, only a handful of countries are represented for each race length; gray shading means there were no data. Despite this limitation, you can still identify which regions rise to the top, and which are a bit slower.
EDIT: Thanks for the feedback regarding missing countries! Because the country codes change and multiple standards are available, several were not joined correctly in the GIS. I’ve fixed as many as I can, so the new map has more countries displayed. Thanks again!
Religious buildings (churches, mosques, synagogues, temples, and other places of worship) often have an intentional orientation, largely to assist with fixing the direction people face when praying. The altar in Christian churches is often pointed toward the liturgical east. Islamic mosques are traditionally oriented toward the Qibla (direction of Mecca).
For these calculations, I selected five countries that are dominated by five different religions (Thailand – Buddhism; Italy – Catholicism; Israel – Judaism; Pakistan – Islam; India – Hinduism). The shapefile containing the Israel buildings was merged with Palestine, which is predominantly Islamic. Though these could be separated, the exact border between the two countries is a bit tenuous, so I opted to leave it as a single region.
The method for the calculation is shown on the graphic. For each building footprint, a bounding rectangle is defined. This rectangle is oriented to minimize its width. The orientation of the building is then measured as the azimuth of the rectangle’s height (longer sides). Orientation is counted in both directions, so a building facing due east is also considered to face west. The plots show the frequency of a given orientation in 5° bins.
As you can see, most religious buildings in these countries are aligned east-west. Pakistan is slightly north of east from Mecca, which may explain why many of the religious buildings there are orientated WSW-ENE.
If you’re a government employee, your salary usually depends on your position and years worked. But it also depends heavily on the state in which you live. Each pair of maps illustrates average annual salaries (extrapolated from one month of full-time payroll in March, 2012) for a specific government function; state government salaries (left-hand maps) are compared to local government salaries (right-hand maps). The scale applies to all maps, so any map can be compared to any other.
Some of the differences are striking because the roles are fundamentally different. For example, in education, most local government employees are grade school teachers, whereas state employees are university professors. Others may be due to how governments allocate their resources or emphasize the importance of a given function. For example, Nevada seems to fund local parks more heavily than other states. Perhaps it’s time for Leslie Knope to leave Pawnee…
This map shows the percentage of each county’s civilian population (aged 18+) who have veteran status. For Census data, as shown here, the term “veteran” is based on the Department of Veteran Affairs’ definition:
A veteran is someone 18 years and older (there are a few 17-year-old veterans) who is not currently on active duty, but who once served on active duty in the United States Army, Navy, Air Force, Marine Corps, or Coast Guard, or who served in the Merchant Marine during World War II. There are many groups whose active service makes them veterans including: those who incurred a service-connected disability during active duty for training in the Reserves or National Guard, even though that service would not otherwise have counted for veteran status; members of a national guard or reserve component who have been ordered to active duty by order of the President or who have a full-time military job. The latter are called AGRs (Active Guard and Reserve). No one who has received a dishonorable discharge is a veteran.
Based on this definition, military personnel on active duty are not counted as veterans, but several paths of active service qualify people for veteran status. As such, military bases will have a notable effect on this map, though not as significant as they could (if those on active duty were counted). For each of the top counties list, I included the names of the largest military installations in the respective county.
Disclaimer – I’ve never read any of the Game of Thrones series (though I do enjoy the show). But my wife has, and has the Jezebel knowledge to make a more informed comment on this graphic. So, in her words…
George R. R. Martin claims that he is a feminist, but there has still been ample debate over whether his popular series, Game of Thrones, reflects those values. While the women of Westeros may strive for power just as the men do, a word-frequency analysis of the books thus far reveals a clear bias towards male terminology. One interesting pattern? In books 4/5, “girl” starts to overtake “boy.” We just may be seeing a future queen.
For all the gamers who love the classic arcade games, here’s a map to guide your Pac-Man efforts. Darker areas are considered more dangerous, as you have a farther distance to travel before reaching an intersection. The lower half of the board is generally considered more difficult to clear, particularly the bottom row, where it is easy to be trapped by ghosts on either side.
There are a couple caveats/glitches, which affect this map. One is that there are four intersections (blue outline) where the ghosts cannot turn upward in scatter and chase modes. Only when frightened can they turn upward at these intersections. There is also the infamous safe spot (hiding spot), outlined in green, where you can sit indefinitely without being touched assuming the ghosts didn’t see you move there.
Back when I was a graduate student, I spent a lot of time as a chess coach and tutor. Because I was teaching at a K-12 school, parents of some of the younger children asked if their kids were ready to play chess. It’s an interesting question, and the answer is different for each person. In general, my experience was that most students could easily learn how the pieces move when they were five, but it took another year before they understood how the pieces work in combination (i.e., strategy).
I was curious about the age at which most board games can be played, so I gathered data from BoardGameGeek (link below). These graphs include data on the 100 board games with the highest number of voters, which I’m interpreting as a proxy for popularity.
In the top left graph, I compare the manufacturer’s suggested minimum age to the players’ suggested minimum age, which is determined by a poll on the website. Out of the 100 games, the ages are the same for 50. In 34 cases, the manufacturer has an older minimum, and in the remaining 16, the players selected an older minimum.
The top right graph shows the slight trend that longer games are generally designed for older players. I’ve noted that it means older players have a longer attention span, but of course, a lot of it has to do with the complexity of the game and strategy, not just how long the player can stay seated at the board.
The bottom left graph suggests that players tend to give newer games higher ratings. I’m not sure I agree that we are creating better board games than we have in the past; as I said, I’m a big chess fan (as well as go…and I’m pretty partial to Carcassonne, which came out in 2000). But there is often a tendency for people to correlate newer with better.
The bottom right graph confirms that popularity is not indicative of quality. At best, this graph shows a weak positive correlation, but many of the highest rated games do not appear in the 100 most popular list.
These graphs were created by dividing the girls growth chart by the boys growth chart. Lower percentiles (blue lines) represent smaller (shorter/lighter) people, while the highest percentiles correspond to larger people. The yellow line represents the typical person (50th percentile = median). Note that the y-axis scales are different for the two graphs; weight ratios vary more significantly than height ratios.
The graphs shows that girl and boy babies are born at close to the same size, but boys get larger more quickly in the first six months of growth. The ratios then increase, approaching one as girls catch up in size. Around the ages of 7-9, the typical girl is about the same size as the typical boy. Then girls hit puberty first, and from 10-13 they are generally larger than boys. Buy once boys hit puberty, they catch up quickly, and become taller and heavier after the age of 13.
To create this map, I derived the average color of each state flag and assigned it to its respective state. Only the obverse side of each flag was used. The notion of average color depends on the color space used; for the purpose of this map, I used a Lab color space (CIELab D50). The background is set to the average color of the USA national flag.
It’s interesting to see that bluer averages tend to be associated with northern states. Redder hues (including purples and pinks) are more southern, and particularly focused in the southeast. The states that chose not to conform to red, white, and blue also stand out (e.g., Washington, New Mexico, Maryland, New Jersey).