A leaflet map for R built on a shape file of US counties

countyfips_leaflet.R

library(sp)
library(rgeos)
library(rgdal)
library(maptools)
library(dplyr)
library(leaflet)
library(scales)
### Begin data prep
# Grab air/water quality data from the EPA
url = "https://data.cdc.gov/api/views/cjae-szjv/rows.csv?accessType=DOWNLOAD"
dat <- read.csv(url, stringsAsFactors = FALSE)
# Colnames tolower
names(dat) <- tolower(names(dat))
dat$countyname <- tolower(dat$countyname)
# Wide data set, subset only what we need.
county_dat <- subset(dat, measureid == "296", 
                     select = c("reportyear","countyfips","statename", "countyname", "value", "unitname")) %>%
    subset(reportyear==2011, select = c("countyfips", "value"))
# Rename columns to make for a clean df merge later.
colnames(county_dat) <- c("GEOID", "airqlty")
# Have to add leading zeos to any FIPS code that's less than 5 digits long to get a good match.
# I'm cheating by using C code. sprintf will work as well.
county_dat$GEOID <- formatC(county_dat$GEOID, width = 5, format = "d", flag = "0")
### End data prep

# Download county shape file from Tiger.
# https://www.census.gov/geo/maps-data/data/cbf/cbf_counties.html
us.map <- readOGR(dsn = ".", layer = "cb_2013_us_county_20m", stringsAsFactors = FALSE)

# Remove Alaska(2), Hawaii(15), Puerto Rico (72), Guam (66), Virgin Islands (78), American Samoa (60)
#  Mariana Islands (69), Micronesia (64), Marshall Islands (68), Palau (70), Minor Islands (74)
us.map <- us.map[!us.map$STATEFP %in% c("02", "15", "72", "66", "78", "60", "69",
                                        "64", "68", "70", "74"),]
# Make sure other outling islands are removed.
us.map <- us.map[!us.map$STATEFP %in% c("81", "84", "86", "87", "89", "71", "76",
                                        "95", "79"),]
# Merge spatial df with downloade ddata.
leafmap <- merge(us.map, county_dat, by=c("GEOID"))

# Format popup data for leaflet map.
popup_dat <- paste0("<strong>County: </strong>", 
                    leafmap$NAME, 
                    "<br><strong>Value: </strong>", 
                    leafmap$airqlty)

pal <- colorQuantile("YlOrRd", NULL, n = 20)
# Render final map in leaflet.
leaflet(data = leafmap) %>% addTiles() %>%
    addPolygons(fillColor = ~pal(airqlty), 
                fillOpacity = 0.8, 
                color = "#BDBDC3", 
                weight = 1,
                popup = popup_dat)

It helped me a lot :-) Thanks

Hi! Thank you for posting this.
Having a small problem and I am new to plotting data such as this. I tried to recreate this as well as use manipulate and use my own data in RStudio and it is crashing. I also got an error about the colorQuantile for "YlOrRd" exceeding the limit of n (n=9 max) before the crash. Any immediate thoughts on why it could be crashing? The dataset you use is significantly larger than mine. Thanks!

Great tutorial. One question, I need to remove other states in the lower 48, how can can I determine the STATEFP id#? Thanks in advance.

when I run

# Download county shape file from Tiger.
# https://www.census.gov/geo/maps-data/data/cbf/cbf_counties.html
us.map <- readOGR(dsn = ".", layer = "cb_2013_us_county_20m", stringsAsFactors = FALSE)

I get: ```
Error in ogrInfo(dsn = dsn, layer = layer, encoding = encoding, use_iconv = use_iconv, :
Cannot open layer

I have the same error with @makis23

Great tutorial!. How do I only display the US map and not show other countries in the background?