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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
# urbnmapr <img src="man/figures/hexsticker.png" align="right" style="width:138.1334px;height:160px;"/>
[](https://travis-ci.org/UrbanInstitute/urbnmapr)
The `urbnmapr` package provides state and county shapefiles in `tibble` format that is compatible to map with `ggplot2`.
Shapefiles include Alaska and Hawaii, transformed to be displayed as insets within the continental United States.
This package is heavily inspired by and derived in part from the [fiftystater package](https://cran.r-project.org/package=fiftystater) by William Murphy. In contrast, `urbnmapr`:
- Uses shapefiles from the US Census Bureau
- Converts the shapefile data to a `tibble` dataframe
- Adds various identifiers for merging
- Includes a county-level shapefile
## Installation
You can install the latest version of `urbnmapr` from GitHub:
```{r installation, message=FALSE, warning=FALSE, eval=FALSE}
# install.packages("devtools")
devtools::install_github("UrbanInstitute/urbnmapr")
```
## Usage
### Quick maps
`urbnmapr` contains two `tibble` dataframes for creating maps:
- `states`
- `counties`
The `states` and `counties` tibbles can be used with `geom_polygon()` and `coord_map()` to create base maps of the continental United States, with Alaska and Hawaii displayed as insets:
```{r blank-state, message=FALSE}
library(tidyverse)
library(urbnmapr)
states %>%
ggplot(aes(long, lat, group = group)) +
geom_polygon(fill = "grey", color = "#ffffff", size = 0.25) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45)
```
```{r blank-county}
counties %>%
ggplot(aes(long, lat, group = group)) +
geom_polygon(fill = "grey", color = "#ffffff", size = 0.05) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45)
```
### More maps
Additional maps can be accessed with `get_urbn_map()`. Use the function to create a tibble in your global environment and then map using the same syntax as above.
```{r get_urbn_map}
territories_counties <- get_urbn_map(map = "territories_counties")
territories_counties %>%
ggplot(aes(long, lat, group = group)) +
geom_polygon(fill = "grey", color = "#ffffff", size = 0.05) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45)
```
### Labels
Labels for all maps can be accessed with `get_urbn_labels()`. Use the function to call the appropriate labels and then label the map with `geom_text()`. Labels can be called inside of `geom_text()`:
```{r quick-labels}
states %>%
ggplot() +
geom_polygon(aes(long, lat, group = group),
fill = "grey", color = "#ffffff", size = 0.25) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
geom_text(data = get_urbn_labels(map = "states"), aes(x = long, lat, label = state_abbv),
size = 3)
```
Or before `geom_text()` is called:
```{r get_urbn_labels}
territories <- get_urbn_map(map = "territories")
labels <- get_urbn_labels(map = "territories")
territories %>%
ggplot() +
geom_polygon(aes(long, lat, group = group),
fill = "grey", color = "#ffffff", size = 0.05) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
geom_text(data = labels, aes(x = long, lat, label = state_abbv), size = 3)
```
## Merging Data
The `states` and `counties` tibbles include various identifiers to simplify merging data. The states `states` tibble contains `state_fips`, `state_abbv`, and `state_name`. The `counties` tibble contains `county_fips`, `state_abbv`, `state_fips`, `county_name`, and `state_name`. Both tibbles can be piped into `ggplot2` to create a choropleth map.
```{r us-choropleth}
statedata %>%
left_join(states, by = "state_name") %>%
ggplot(mapping = aes(long, lat, group = group, fill = horate)) +
geom_polygon(color = "#ffffff", size = .25) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
labs(fill = "Homeownership rate")
```
```{r county}
household_data <- left_join(countydata, counties, by = "county_fips")
household_data %>%
ggplot(aes(long, lat, group = group, fill = medhhincome)) +
geom_polygon(color = "#ffffff", size = 0.05) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45)
```
## Styles
`library(urbnmapr)` works well with the [Urban Institute `ggplot2` theme.](https://github.com/UrbanInstitute/urban_R_theme)
```{r load-theme, message=FALSE}
library(urbnthemes)
set_urbn_defaults(style = "map")
```
```{r theme-state}
statedata %>%
left_join(states, by = "state_name") %>%
ggplot(mapping = aes(long, lat, group = group, fill = horate)) +
geom_polygon(color = "#ffffff", size = .25) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
scale_fill_gradientn(labels = scales::percent) +
labs(fill = "Homeownership rate")
```
```{r theme-counties}
household_data %>%
filter(state_name %in% c("Virginia", "Maryland", "District of Columbia")) %>%
ggplot(aes(long, lat, group = group, fill = medhhincome)) +
geom_polygon(color = "#ffffff", size = 0.05) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
scale_fill_gradientn(labels = scales::dollar) +
labs(fill = "Median household income")
```
## License
Code released under the GNU General Public License v3.0.
## Code of conduct
Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.