What are the most educated counties in the US?
CENSUS DATA ON EDUCATIONAL ATTAINMENT BY COUNTY
People ask us “what are the most educated counties in the USA”? It turns out the census keeps track of this sort of thing. We found a table called ACS_14_1YR_S1501.csv in the American Community Survey; look for stuff on educational attainment by county. And it was an easy bit of R to get the answers. We computed two things:
- The percentage of the 25 and older population with a graduate or professional degree
- The percentage of the population (of any age) with a bachelor’s degree or higher
Here’s how it came out:
Top US counties by percentage of people 25 and up with graduate or professional degrees in 2014:
| Rank | County | % with graduate degree |
|---|---|---|
| 1 | Arlington County, Virginia | 36.70 |
| 2 | Alexandria city, Virginia | 32.90 |
| 3 | Montgomery County, Maryland | 31.60 |
| 4 | District of Columbia, District of Columbia | 30.60 |
| 5 | Howard County, Maryland | 30.50 |
| 6 | Fairfax County, Virginia | 30.20 |
| 7 | Orange County, North Carolina | 30.00 |
| 8 | New York County, New York | 28.50 |
| 9 | Tompkins County, New York | 28.40 |
| 10 | Washtenaw County, Michigan | 28.30 |
| 11 | Boulder County, Colorado | 26.90 |
| 12 | Story County, Iowa | 26.00 |
| 13 | Middlesex County, Massachusetts | 25.70 |
| 14 | Marin County, California | 25.60 |
| 15 | Albemarle County, Virginia | 25.40 |
| 16 | Benton County, Oregon | 25.30 |
| 17 | Monroe County, Indiana | 25.20 |
| 18 | Loudoun County, Virginia | 24.80 |
| 19 | Riley County, Kansas | 23.90 |
| 20 | Johnson County, Iowa | 23.80 |
| 21 | Westchester County, New York | 23.60 |
| 22 | Somerset County, New Jersey | 23.50 |
| 23 | James City County, Virginia | 23.30 |
| 24 | Norfolk County, Massachusetts | 23.10 |
| 25 | Santa Clara County, California | 22.30 |
Top US counties by percentage of people with Bachelors degrees or higher in 2014:
| Rank | County | % with Bachelors or higher |
|---|---|---|
| 1 | Arlington County, Virginia | 71.50 |
| 2 | Alexandria city, Virginia | 62.80 |
| 3 | Fairfax County, Virginia | 60.30 |
| 4 | Howard County, Maryland | 59.90 |
| 5 | New York County, New York | 59.90 |
| 6 | Loudoun County, Virginia | 58.70 |
| 7 | Montgomery County, Maryland | 58.50 |
| 8 | Boulder County, Colorado | 58.00 |
| 9 | Douglas County, Colorado | 56.50 |
| 10 | Hamilton County, Indiana | 56.30 |
| 11 | Williamson County, Tennessee | 56.10 |
| 12 | Marin County, California | 55.20 |
| 13 | District of Columbia, District of Columbia | 55.00 |
| 14 | Orange County, North Carolina | 55.00 |
| 15 | San Francisco County, California | 54.20 |
| 16 | Somerset County, New Jersey | 53.70 |
| 17 | Johnson County, Iowa | 53.60 |
| 18 | Benton County, Oregon | 53.50 |
| 19 | Washtenaw County, Michigan | 53.00 |
| 20 | Morris County, New Jersey | 53.00 |
| 21 | Johnson County, Kansas | 52.80 |
| 22 | Tompkins County, New York | 52.40 |
| 23 | Middlesex County, Massachusetts | 52.30 |
| 24 | Delaware County, Ohio | 52.20 |
| 25 | Norfolk County, Massachusetts | 51.90 |
R Code to follow along at home
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| library(dplyr) | |
| library(xtable) | |
| #HC01_EST_VC17 | |
| #Total; Estimate; Percent bachelor's degree or higher | |
| #HC01_EST_VC14 | |
| #Total; Estimate; Population 25 years and over - Graduate or professional degree | |
| #Note: I stripped out a second header line in preproc | |
| df <- read.csv("ACS_14_1YR_S1501.csv") | |
| #Keep only the necessary columns, give readable names | |
| df=df %>% select(GEO.display.label, HC01_EST_VC17, HC01_EST_VC14) | |
| names(df)=c("County","Bachelors_or_Higher","Grad_Degree") | |
| #Make a small data frame sorted by grad degree | |
| sdf = data.frame( | |
| df %>% arrange(desc(Grad_Degree)) %>% select(County, Grad_Degree) | |
| )[1:25,] | |
| print(xtable(sdf), type="html") | |
| #Make a small data frame sorted by Bachelors or higher | |
| sdf= data.frame( | |
| df %>% arrange(desc(Bachelors_or_Higher)) %>% select(County, Bachelors_or_Higher) | |
| )[1:25,] | |
| print(xtable(sdf), type="html") |
by Photo credit: https://flic.kr/p/aQM3Z
What is the effect of the size of the counties? None of the “most educated” counties are in the west which in general, have larger, possibly more diverse counties.
April 16, 2016 @ 12:07 pm
It’s not a coincidence that the top counties are of, or adjacent to, government centers. Red stater or Blue stater, the government pays more for educated staff. Whether said staff is needed or utilized is another question.
April 16, 2016 @ 7:02 pm