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First, we need to install and load the tidycensus package.

install.packages('tidycensus')
library(tidycensus)

Visualizing margins of error (MOE)

# Write and run code here
# Request median household income data
maine_inc <- get_acs(geography = "county", 
                     variables = c(hhincome = "B19013_001"), 
                     state = "ME")
# Generate horizontal error bars with dots
ggplot(maine_inc, aes(x = estimate, y = NAME)) + 
  geom_errorbarh(aes(xmin = estimate - moe, xmax = estimate + moe)) + 
  geom_point()
# Remove unnecessary content from the county's name
maine_inc2 <- maine_inc %>%
  mutate(NAME = str_replace(NAME, " County, Maine", ""))

# Build a margin of error plot incorporating your modifications
ggplot(maine_inc2, aes(x = estimate, y = reorder(NAME, estimate))) + 
  geom_errorbarh(aes(xmin = estimate - moe, xmax = estimate + moe)) + 
  geom_point(size = 3, color = "darkgreen") + 
  theme_grey(base_size = 14) + 
  labs(title = "Median household income", 
       subtitle = "Counties in Maine", 
       x = "ACS estimate (bars represent margins of error)", 
       y = "") + 
  scale_x_continuous(labels = scales::dollar)

US Census geographic data

install.packages('tigris')
library(tigris)
# Get a counties dataset for Colorado and plot it
co_counties <- counties(state = "CO")
plot(co_counties)
# Get a Census tracts dataset for Denver County, Colorado and plot it
denver_tracts <- tracts(state = "CO", county = "Denver")
plot(denver_tracts)
# Plot area water features for Lane County, Oregon
lane_water <- area_water(state = "OR", county = "Lane")
plot(lane_water)
# Plot primary & secondary roads for the state of New Hampshire
nh_roads <- primary_secondary_roads(state = "NH")
plot(nh_roads)

TIGER/Line and cartographic boundary files

# Get a counties dataset for Michigan
mi_tiger <- counties("MI")

# Get the equivalent cartographic boundary shapefile
mi_cb <- counties("MI", cb = TRUE)

# Overlay the two on a plot to make a comparison
plot(mi_tiger)
plot(mi_cb, add = TRUE, border = "red")
# Get data from tigris as simple features
options(tigris_class = "sf")

# Get countries from Colorado and view the first few rows
colorado_sf <- counties("CO")
head(colorado_sf)

# Plot its geometry column
plot(colorado_sf$geometry)
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