A simple solution to a common problem

urbnmapr makes a few variations of the same basic map.

Installation

The package lives on GitHub. The devtools package makes it easy to install straight from the source.

devtools::install_github("UrbanInstitute/urbnmapr")

Functionality

states <- get_urbn_map(map = "states", sf = TRUE)

##   state_fips state_abbv state_name                       geometry
## 1         01         AL    Alabama MULTIPOLYGON (((1150023 -15...
## 2         02         AK     Alaska MULTIPOLYGON (((-1273178 -2...
## 3         04         AZ    Arizona MULTIPOLYGON (((-1386136 -1...
## 4         05         AR   Arkansas MULTIPOLYGON (((482001 -928...
## 5         06         CA California MULTIPOLYGON (((-1717278 -1...

You can merge your data onto this dataframe to make choropleth maps.

geographic_data <- left_join(states, statedata, 
                             by = "state_name")

Making maps

ggplot() +
  geom_sf(data = geographic_data,
          mapping = aes(fill = medhhincome),
          color = "white") +
  scale_fill_gradientn(labels = scales::dollar) +
  coord_sf(datum = NA) +
  urbnthemes::theme_urbn_map() +
  labs(fill = "Median household income")

Extensions

For more information

Visit the urbnmapr GitHub page for more detailed instructions.

The Urban Institute mapping guide is currently in progress!

Why R?

• Reproducibility

• Make the same map 100 times

• It’s free

• Geospatial analysis in R is constantly evolving

Why a package?

• Portable

• Lowers the barrier to entry

• Push updates when we need to

• Cool hex stickers

R @ Urban

We create tools to help researchers do their jobs more efficiently- whether it is running trainings, building packages, or writing detailed guides.

You can follow along:

• Check out our website
• Sign up for the urbnverse list serve (we won’t email you more than once a month!)
• Look for new posts on Data@Urban, the Urban Institute’s behind-the-scenes blog on data, code, and more.
• Email me at sstrochak@urban.org for more information!