Not a crescent: education patterns in the North East

This blog is becoming increasingly about two numbers: the high school graduation rate and college graduation rates of counties in the US. This could just be my peculiar obsession, but these two numbers together do tell a lot about a county.
It is harder to add them up across states, since "counties" have many different meanings in different states. In the eastern part of the US, counties are much smaller in area, and often much smaller in population.

After I did the Western states, I went through and entered the information for the New England/Middle Atlantic states. Which, for my purposes, are: Maine, Massachusetts, New Hampshire, Vermont, New York, Connecticut, New Jersey, Pennsylvania, Delaware, and Maryland. These states all have relative small numbers of counties, and they also share common demographics, which makes them a good set to compare amongst.
The first thing of interest is that this is not a crescent: the Northeast doesn't seem to have many areas that have high highschool rates and low college rates. It seems to have more of a traditional X=Y relationship. I am also wondering if perhaps I chose the best grouping of states: it seems that what does occur in the lower right might be based heavily around rural Pennsylvania.
Another obvious thing is that there is one major grouping of states, and then a bunch of points to the left. The points to the left make up some really significant outliers. They consist of Sussex County (Boston), three of New York City's burroughs, Philadelphia County and Baltimore City. As could be expected, big metropolitan areas pull in both college educated people, and non-high school educated people.
Also, notice the trio at the top right: two counties in Maryland, just outside of Washington, DC, and Thompkins County, home of Cornell University.

Hispanic education in California's counties:

As I mentioned in the New Mexico post, sometimes while scanning through data, I notice certain patterns, and then later on I get curious enough to do the data entry and see if they are true.
One pattern I have noticed is that counties with high Hispanic populations also have low high school graduation rates. So I decided to actually do the data and see if it proved true:The data lines up surprisingly well, which data very rarely does. There are different ways to analyze this data, and some of them are pretty politically and socially charged. Another is that often this is an artifact: heavily Hispanic counties tend to be big, economically active counties that attract workers of every stripe.
And while you are thinking about that, we can also think about this:Here, there is not a lot of real correlation. The biggest story here is that the cluster of counties that were at the bottom right are now at the bottom left. Much of California is like the rest of the Western states, where you have a lot of counties with high high school rates and low college rates. So again, as with so much, we have three quadrants filled up in the college diagram.

Anyway, while this is marinating, I am still working on my MASTER PLAN.

Making these things is hard: a special treat for my viewers. Both of you.

One of the problems with scatterplots is that for the most part, you can only plot two variables.

But, to quote RZA: "The fourth dimension is time, it comes alive, when the chakras energize up the back of your spine"

Or, in this case, the third dimension comes alive with a BADLY MADE ANIMATED GIF.
I am so proud of my animated gif, or rather proud of the idea and ashamed of the execution, that I don't know tooooo much to say about this, besides WTF California?

New Mexico, and the ALMOST joy of having a wildly counterintuitive result

While entering some other data, I had a chance to see that on paper, much as in real life, New Mexico is perhaps one of the most nuanced and diverse of states. Specifically, New Mexico has a high percentage of people who do not speak English at home. And in many places, a low percentage of people who are foreign born. I wanted to look at these numbers more closely, and I got:
It would be awesome if I could say there is a negative correlation between English speaking and native born people, but actually there is...no correlation. Don't let the blue line fool you, its very gradual slope is close enough to flat.
If I knew more about New Mexico, I could probably make more sense out of this.

Sneak preview!

I have been working on something.
Here it is!Okay, it is pretty obvious what this probably is, but more later!

Not a crescent

In the Grand Crescent post, I postulated that Denver, as an outlier, was where it was because Denver County (which is also Denver City) would be following more the pattern of a large metropolis, then following the pattern of a county in a western state.

I just made that up when I typed it, but it sounded good.

But of course, then I started wondering, so I wanted to plot the high school versus college rates of some of the US' biggest cities. I chose 30 as my number (mostly so Portland could be on there), and started digging for data.
Cities, as demographic units, are not very good. There tends to be lots of artifacts in the data, depending on how the city borders are drawn. Two metro areas might have similar demographics, but the largest city in both of them might exclude or include suburbs. For example, Detroit metro and Portland metro might be more similar than someone would guess, but whereas many of Portland's wealthy areas (The West Hills for example) are included in the city, in Detroit those areas are, I believe, separate suburbs. So this data has problems. All data has problems.
The first thing to notice about this data:
NOT A CRESCENT.
It has a more predictable X=Y shape, although one that is spread out irregularly.
There seems to be a little bit of evidence that parts of the Western States are both well educated, and egalitarian about it. Not a lot, though. Although the five cities in the upper right do have two things in common: they are smaller, and they are outside the most traditional urbanized areas of the United States.
Actually, the most obvious thing that jumps out at me is size, which I should probably do another plot for. NYC, LA, Chicago and Houston, the 4 biggest cities, are all clustered pretty close together. They all have low education levels, and within what they do have, are more "elitist" in the sense of having lots of college graduates for the amount of high school graduates.
I actually am probably going to run plots on these numbers for a number of different factors. Sometimes soon!

Drivers licenses and rurality.

An intuitive conclusion to draw is that people are more dependent on cars in rural areas. According to anecdotes, New York City is one of the few places where it is normal for an adult to not drive.
Ah, but what does the data say about this intuitive idea?As usual, it says that this idea is not quite that absolute. There is a trend in that direction, but it is quite outdone by other things. New York and Connecticut are a good example: both are urbanized states, with much of Connecticut laying inside the NYC metro area. And yet there numbers of licensed drivers seems quite heavy.
(For whatever reason, Vermont and Alabama have more licensed drivers than they have driving age population, which could be an artifact of keeping their system updated, or could mean there are people who have fraudulent licenses)