library(tidycensus)
## Warning: package 'tidycensus' was built under R version 3.4.3
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 3.4.3
## -- Attaching packages ------------------------------------------- tidyverse 1.2.1 --
## v ggplot2 2.2.1 v purrr 0.2.4
## v tibble 1.3.4 v dplyr 0.7.4
## v tidyr 0.7.2 v stringr 1.2.0
## v readr 1.1.1 v forcats 0.2.0
## Warning: package 'ggplot2' was built under R version 3.4.3
## Warning: package 'tidyr' was built under R version 3.4.3
## Warning: package 'dplyr' was built under R version 3.4.3
## -- Conflicts ---------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
#testing
census_api_key("687a401e65631b92defbc1c5d41c7668705d2bbd")
## To install your API key for use in future sessions, run this function with `install = TRUE`.
m90 <- get_decennial(geography = "state", variables = "H043A001", year = 1990)
## [1] "Checking SF3 API for data..."
m90 %>%
ggplot(aes(x = value, y = reorder(NAME, value))) +
geom_point()
nh <- get_acs(geography = "county", variables = "B19013_001", state = "NH")
head(nh)
## # A tibble: 6 x 5
## GEOID NAME variable estimate moe
## <chr> <chr> <chr> <dbl> <dbl>
## 1 33001 Belknap County, New Hampshire B19013_001 62159 2383
## 2 33003 Carroll County, New Hampshire B19013_001 53306 2643
## 3 33005 Cheshire County, New Hampshire B19013_001 57782 1690
## 4 33007 Coos County, New Hampshire B19013_001 42312 1911
## 5 33009 Grafton County, New Hampshire B19013_001 55762 2055
## 6 33011 Hillsborough County, New Hampshire B19013_001 71244 998
nh %>%
mutate(NAME = gsub(" County, New Hampshire", "", NAME)) %>%
ggplot(aes(x = estimate, y = reorder(NAME, estimate))) +
geom_errorbarh(aes(xmin = estimate - moe, xmax = estimate + moe)) +
geom_point(color = "red", size = 3) +
labs(title = "Household income by county in New Hampshire",
subtitle = "2011-2015 American Community Survey",
y = "",
x = "ACS estimate (bars represent margin of error)")
#testing
p <- data.frame(get_acs
(geography = "county", variables = "B19013_001", state = "NH"))
head(p)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B19013_001 62159 2383
## 2 33003 Carroll County, New Hampshire B19013_001 53306 2643
## 3 33005 Cheshire County, New Hampshire B19013_001 57782 1690
## 4 33007 Coos County, New Hampshire B19013_001 42312 1911
## 5 33009 Grafton County, New Hampshire B19013_001 55762 2055
## 6 33011 Hillsborough County, New Hampshire B19013_001 71244 998
e <- (p[,4])
head(e)
## [1] 62159 53306 57782 42312 55762 71244
summary(e)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 42312 55830 59247 60649 65027 81198
#median age less than 41
age <- data.frame(get_acs(geography = "county", variables = "B01002_001E"
, state = "NH"))
head(age)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B01002_001 46.1 0.3
## 2 33003 Carroll County, New Hampshire B01002_001 50.3 0.2
## 3 33005 Cheshire County, New Hampshire B01002_001 42.0 0.3
## 4 33007 Coos County, New Hampshire B01002_001 48.1 0.3
## 5 33009 Grafton County, New Hampshire B01002_001 41.9 0.3
## 6 33011 Hillsborough County, New Hampshire B01002_001 40.1 0.2
tail(age)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B01002_001 41.9 0.3
## 6 33011 Hillsborough County, New Hampshire B01002_001 40.1 0.2
## 7 33013 Merrimack County, New Hampshire B01002_001 42.6 0.2
## 8 33015 Rockingham County, New Hampshire B01002_001 43.5 0.1
## 9 33017 Strafford County, New Hampshire B01002_001 37.2 0.3
## 10 33019 Sullivan County, New Hampshire B01002_001 45.1 0.3
#% of people with degree in 75th precentile
#some college or associate
assc <- data.frame((get_acs(geography = "county", variable = "B06009_004E"
, state = "NH")))
head(assc)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B06009_004 13494 614
## 2 33003 Carroll County, New Hampshire B06009_004 10756 680
## 3 33005 Cheshire County, New Hampshire B06009_004 14058 680
## 4 33007 Coos County, New Hampshire B06009_004 7311 374
## 5 33009 Grafton County, New Hampshire B06009_004 15588 663
## 6 33011 Hillsborough County, New Hampshire B06009_004 78616 1604
tail(assc)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B06009_004 15588 663
## 6 33011 Hillsborough County, New Hampshire B06009_004 78616 1604
## 7 33013 Merrimack County, New Hampshire B06009_004 31019 808
## 8 33015 Rockingham County, New Hampshire B06009_004 61894 1540
## 9 33017 Strafford County, New Hampshire B06009_004 24002 921
## 10 33019 Sullivan County, New Hampshire B06009_004 8159 501
#bachelors degree
bach <- data.frame((get_acs(geography = "county", variables = "B06009_005E",
state = "NH")))
head(bach)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B06009_005 8412 522
## 2 33003 Carroll County, New Hampshire B06009_005 7279 512
## 3 33005 Cheshire County, New Hampshire B06009_005 10128 587
## 4 33007 Coos County, New Hampshire B06009_005 2827 220
## 5 33009 Grafton County, New Hampshire B06009_005 12404 642
## 6 33011 Hillsborough County, New Hampshire B06009_005 64234 1632
tail(bach)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B06009_005 12404 642
## 6 33011 Hillsborough County, New Hampshire B06009_005 64234 1632
## 7 33013 Merrimack County, New Hampshire B06009_005 22168 836
## 8 33015 Rockingham County, New Hampshire B06009_005 52427 1614
## 9 33017 Strafford County, New Hampshire B06009_005 17024 877
## 10 33019 Sullivan County, New Hampshire B06009_005 5145 381
#graduate professional degree
grad <- data.frame((get_acs(geography = "county", variables = "B06009_006E",
state = "NH")))
head(grad)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B06009_006 4606 407
## 2 33003 Carroll County, New Hampshire B06009_006 4388 398
## 3 33005 Cheshire County, New Hampshire B06009_006 6373 455
## 4 33007 Coos County, New Hampshire B06009_006 1465 177
## 5 33009 Grafton County, New Hampshire B06009_006 11021 553
## 6 33011 Hillsborough County, New Hampshire B06009_006 35770 1111
tail(grad)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B06009_006 11021 553
## 6 33011 Hillsborough County, New Hampshire B06009_006 35770 1111
## 7 33013 Merrimack County, New Hampshire B06009_006 13303 652
## 8 33015 Rockingham County, New Hampshire B06009_006 30137 1165
## 9 33017 Strafford County, New Hampshire B06009_006 10464 688
## 10 33019 Sullivan County, New Hampshire B06009_006 3171 379
#% of jobs in high wage services
#with income $75,000 or more
high <- data.frame((get_acs(geography = "county", variables = "B06010_011E",
state = "NH")))
head(high)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B06010_011 5548 398
## 2 33003 Carroll County, New Hampshire B06010_011 4255 401
## 3 33005 Cheshire County, New Hampshire B06010_011 6178 395
## 4 33007 Coos County, New Hampshire B06010_011 1344 164
## 5 33009 Grafton County, New Hampshire B06010_011 9152 537
## 6 33011 Hillsborough County, New Hampshire B06010_011 53237 1335
tail(high)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B06010_011 9152 537
## 6 33011 Hillsborough County, New Hampshire B06010_011 53237 1335
## 7 33013 Merrimack County, New Hampshire B06010_011 15983 690
## 8 33015 Rockingham County, New Hampshire B06010_011 47277 1412
## 9 33017 Strafford County, New Hampshire B06010_011 12404 648
## 10 33019 Sullivan County, New Hampshire B06010_011 3546 313
still need income volatility, gain in high wage services, gain in people 17 and under, within 1 hr of major airport, income volatility
#Farmers, ranchers, and other agricultural managers (returns NA)
#Farm employment, farm earnings, farm earnings above 5+ years
farm <- data.frame((get_acs(geography = "county", variables = "B24121_017E"
, state = "NH")))
head(farm)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B24121_017 NA NA
## 2 33003 Carroll County, New Hampshire B24121_017 NA NA
## 3 33005 Cheshire County, New Hampshire B24121_017 NA NA
## 4 33007 Coos County, New Hampshire B24121_017 NA NA
## 5 33009 Grafton County, New Hampshire B24121_017 NA NA
## 6 33011 Hillsborough County, New Hampshire B24121_017 NA NA
tail(farm)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B24121_017 NA NA
## 6 33011 Hillsborough County, New Hampshire B24121_017 NA NA
## 7 33013 Merrimack County, New Hampshire B24121_017 NA NA
## 8 33015 Rockingham County, New Hampshire B24121_017 NA NA
## 9 33017 Strafford County, New Hampshire B24121_017 NA NA
## 10 33019 Sullivan County, New Hampshire B24121_017 NA NA
#90th percentile farm earnings, missing data
farm_bls <- data.frame(read.csv("BLS.csv", header = TRUE))
head(farm_bls)
## Area.Name
## 1 Bakersfield, CA(0012540)
## 2 Boise City, ID(0014260)
## 3 Chicago-Naperville-Arlington Heights, IL Metropolitan Division(0016974)
## 4 Chicago-Naperville-Elgin, IL-IN-WI(0016980)
## 5 Columbus, OH(0018140)
## 6 Fresno, CA(0023420)
## X90th_percentile
## 1 130090
## 2 -
## 3 98360
## 4 103690
## 5 127780
## 6 159280
#farming fishing and forestry occupations https://data.bls.gov/oes/#/geoOcc/Multiple%20occupations%20for%20one%20geographical%20area
#complete data just needs to all be done out in excel by county and state merged together
#https://cran.r-project.org/web/packages/blsAPI/blsAPI.pdf BLS package
#worked outside any metropolitan statistical area
rural <- data.frame((get_acs(geography = "county", variables = "B08016_012E"
, state = "NH")))
head(rural)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B08016_012 0 26
## 2 33003 Carroll County, New Hampshire B08016_012 0 23
## 3 33005 Cheshire County, New Hampshire B08016_012 0 26
## 4 33007 Coos County, New Hampshire B08016_012 0 23
## 5 33009 Grafton County, New Hampshire B08016_012 0 26
## 6 33011 Hillsborough County, New Hampshire B08016_012 78 58
tail(rural)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B08016_012 0 26
## 6 33011 Hillsborough County, New Hampshire B08016_012 78 58
## 7 33013 Merrimack County, New Hampshire B08016_012 0 26
## 8 33015 Rockingham County, New Hampshire B08016_012 0 26
## 9 33017 Strafford County, New Hampshire B08016_012 0 26
## 10 33019 Sullivan County, New Hampshire B08016_012 0 23
#Natural resources, construction, and maintenance occup
natural <- data.frame((get_acs(geography = "county", variables = "C24050_057E"
, state = "NH")))
head(natural)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire C24050_057 3387 311
## 2 33003 Carroll County, New Hampshire C24050_057 2728 352
## 3 33005 Cheshire County, New Hampshire C24050_057 3859 395
## 4 33007 Coos County, New Hampshire C24050_057 1684 168
## 5 33009 Grafton County, New Hampshire C24050_057 3887 312
## 6 33011 Hillsborough County, New Hampshire C24050_057 17902 950
tail(natural)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire C24050_057 3887 312
## 6 33011 Hillsborough County, New Hampshire C24050_057 17902 950
## 7 33013 Merrimack County, New Hampshire C24050_057 6956 558
## 8 33015 Rockingham County, New Hampshire C24050_057 15092 820
## 9 33017 Strafford County, New Hampshire C24050_057 5652 526
## 10 33019 Sullivan County, New Hampshire C24050_057 1987 241
#Geographical Mobility in the Past Year by Age
mobility <- data.frame((get_acs(geography = "county", variables = "B07001_001E"
, state = "NH")))
head(mobility)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07001_001 59975 146
## 2 33003 Carroll County, New Hampshire B07001_001 47103 159
## 3 33005 Cheshire County, New Hampshire B07001_001 75784 163
## 4 33007 Coos County, New Hampshire B07001_001 31580 83
## 5 33009 Grafton County, New Hampshire B07001_001 88584 126
## 6 33011 Hillsborough County, New Hampshire B07001_001 399742 378
tail(mobility)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07001_001 88584 126
## 6 33011 Hillsborough County, New Hampshire B07001_001 399742 378
## 7 33013 Merrimack County, New Hampshire B07001_001 146202 161
## 8 33015 Rockingham County, New Hampshire B07001_001 296177 352
## 9 33017 Strafford County, New Hampshire B07001_001 124160 201
## 10 33019 Sullivan County, New Hampshire B07001_001 42820 113
#a lot of different migration pattern data available by age and education
#Median income in the past 12 months --!!Total:
income <- data.frame((get_acs(geography = "county", variables = "B06011_001E"
, state = "NH")))
head(income)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B06011_001 30588 727
## 2 33003 Carroll County, New Hampshire B06011_001 27887 1558
## 3 33005 Cheshire County, New Hampshire B06011_001 26974 669
## 4 33007 Coos County, New Hampshire B06011_001 23182 874
## 5 33009 Grafton County, New Hampshire B06011_001 26820 825
## 6 33011 Hillsborough County, New Hampshire B06011_001 33403 557
tail(income)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B06011_001 26820 825
## 6 33011 Hillsborough County, New Hampshire B06011_001 33403 557
## 7 33013 Merrimack County, New Hampshire B06011_001 31745 576
## 8 33015 Rockingham County, New Hampshire B06011_001 37149 547
## 9 33017 Strafford County, New Hampshire B06011_001 26324 680
## 10 33019 Sullivan County, New Hampshire B06011_001 28760 1689
#Median income in the past 12 months --!!Total:
income <- data.frame((get_acs(geography = "county", variables = "B07011_001E"
, state = "NH")))
head(income)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07011_001 NA NA
## 2 33003 Carroll County, New Hampshire B07011_001 27887 1558
## 3 33005 Cheshire County, New Hampshire B07011_001 NA NA
## 4 33007 Coos County, New Hampshire B07011_001 23182 874
## 5 33009 Grafton County, New Hampshire B07011_001 26820 825
## 6 33011 Hillsborough County, New Hampshire B07011_001 NA NA
tail(income)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07011_001 26820 825
## 6 33011 Hillsborough County, New Hampshire B07011_001 NA NA
## 7 33013 Merrimack County, New Hampshire B07011_001 31745 576
## 8 33015 Rockingham County, New Hampshire B07011_001 37149 547
## 9 33017 Strafford County, New Hampshire B07011_001 26324 680
## 10 33019 Sullivan County, New Hampshire B07011_001 NA NA
#Total living in area 1 year ago:
migration <- data.frame((get_acs(geography = "county",
variables = "B07410_001E", state = "NH")))
head(migration)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07410_001 51097 623
## 2 33003 Carroll County, New Hampshire B07410_001 41278 632
## 3 33005 Cheshire County, New Hampshire B07410_001 62265 700
## 4 33007 Coos County, New Hampshire B07410_001 27340 380
## 5 33009 Grafton County, New Hampshire B07410_001 73835 956
## 6 33011 Hillsborough County, New Hampshire B07410_001 330925 1591
tail(migration)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07410_001 73835 956
## 6 33011 Hillsborough County, New Hampshire B07410_001 330925 1591
## 7 33013 Merrimack County, New Hampshire B07410_001 122653 997
## 8 33015 Rockingham County, New Hampshire B07410_001 250238 1392
## 9 33017 Strafford County, New Hampshire B07410_001 101026 1096
## 10 33019 Sullivan County, New Hampshire B07410_001 35828 450
#Total living in area 1 year ago:!!No income
youth <- data.frame((get_acs(geography = "county",
variables = "B07410_002E", state = "NH")))
head(youth)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07410_002 5136 516
## 2 33003 Carroll County, New Hampshire B07410_002 3079 375
## 3 33005 Cheshire County, New Hampshire B07410_002 4355 360
## 4 33007 Coos County, New Hampshire B07410_002 1794 203
## 5 33009 Grafton County, New Hampshire B07410_002 6785 606
## 6 33011 Hillsborough County, New Hampshire B07410_002 32265 1259
tail(youth)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07410_002 6785 606
## 6 33011 Hillsborough County, New Hampshire B07410_002 32265 1259
## 7 33013 Merrimack County, New Hampshire B07410_002 12269 773
## 8 33015 Rockingham County, New Hampshire B07410_002 19811 933
## 9 33017 Strafford County, New Hampshire B07410_002 7544 548
## 10 33019 Sullivan County, New Hampshire B07410_002 2908 298
#Total living in area 1 year ago:!!With income:
migrate <- data.frame((get_acs(geography = "county",
variables = "B07410_003E", state = "NH")))
head(migrate)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07410_003 45961 736
## 2 33003 Carroll County, New Hampshire B07410_003 38199 671
## 3 33005 Cheshire County, New Hampshire B07410_003 57910 678
## 4 33007 Coos County, New Hampshire B07410_003 25546 359
## 5 33009 Grafton County, New Hampshire B07410_003 67050 901
## 6 33011 Hillsborough County, New Hampshire B07410_003 298660 1816
tail(migrate)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07410_003 67050 901
## 6 33011 Hillsborough County, New Hampshire B07410_003 298660 1816
## 7 33013 Merrimack County, New Hampshire B07410_003 110384 1174
## 8 33015 Rockingham County, New Hampshire B07410_003 230427 1605
## 9 33017 Strafford County, New Hampshire B07410_003 93482 1227
## 10 33019 Sullivan County, New Hampshire B07410_003 32920 485
#Total living in area 1 year ago:!!With income:!!$1 to $9,999
youth_3 <- data.frame((get_acs(geography = "county",
variables = "B07410_004E", state = "NH")))
head(youth_3)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B07410_004 7409 633
## 2 33003 Carroll County, New Hampshire B07410_004 7395 586
## 3 33005 Cheshire County, New Hampshire B07410_004 11064 656
## 4 33007 Coos County, New Hampshire B07410_004 5340 389
## 5 33009 Grafton County, New Hampshire B07410_004 13599 759
## 6 33011 Hillsborough County, New Hampshire B07410_004 50101 1293
tail(youth_3)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B07410_004 13599 759
## 6 33011 Hillsborough County, New Hampshire B07410_004 50101 1293
## 7 33013 Merrimack County, New Hampshire B07410_004 19500 951
## 8 33015 Rockingham County, New Hampshire B07410_004 36282 1092
## 9 33017 Strafford County, New Hampshire B07410_004 19781 1116
## 10 33019 Sullivan County, New Hampshire B07410_004 5425 444
y <- data.frame(rbind())
#Living in a principal city:
city <- data.frame((get_acs(geography = "county",
variables = "B08016_002E", state = "NH")))
head(city)
## GEOID NAME variable estimate moe
## 1 33001 Belknap County, New Hampshire B08016_002 0 26
## 2 33003 Carroll County, New Hampshire B08016_002 0 23
## 3 33005 Cheshire County, New Hampshire B08016_002 0 26
## 4 33007 Coos County, New Hampshire B08016_002 0 23
## 5 33009 Grafton County, New Hampshire B08016_002 0 26
## 6 33011 Hillsborough County, New Hampshire B08016_002 102301 1319
tail(city)
## GEOID NAME variable estimate moe
## 5 33009 Grafton County, New Hampshire B08016_002 0 26
## 6 33011 Hillsborough County, New Hampshire B08016_002 102301 1319
## 7 33013 Merrimack County, New Hampshire B08016_002 0 26
## 8 33015 Rockingham County, New Hampshire B08016_002 0 26
## 9 33017 Strafford County, New Hampshire B08016_002 0 26
## 10 33019 Sullivan County, New Hampshire B08016_002 0 23