For the assignemt I’ve downloaded and pre-processed the locations of air quality monitors in United States. Their location is shown on the map by type, multiple type sensors have a separate category. The map siplay uses the “clustered markers” feature of Leaflet.
# Download data
if(!file.exists("annual_conc_by_monitor_2017.csv")) {
if(!file.exists("annual_conc_by_monitor_2017.zip")) {
download.file("https://aqs.epa.gov/aqsweb/airdata/annual_conc_by_monitor_2017.zip",
destfile = "annual_conc_by_monitor_2017.zip")
}
unzip("annual_conc_by_monitor_2017.zip")
}
# Process selected monitor data
library(dplyr)
anc_sub <- tbl_df(read.csv("annual_conc_by_monitor_2017.csv")) %>%
filter(Parameter.Name %in% c("PM2.5 - Local Conditions", "Ozone", "Sulfur dioxide")) %>%
select(Latitude,Longitude,Parameter.Name) %>%
distinct() %>%
group_by(Latitude, Longitude) %>%
summarise(Monitored.params = paste(Parameter.Name, collapse = ", ")) %>%
mutate(Color = "none") %>%
mutate(Color = ifelse(Monitored.params == "PM2.5 - Local Conditions", "red",
ifelse(Monitored.params == "Sulfur dioxide", "yellow",
ifelse(Monitored.params == "Ozone", "blue", "orange"))))