Using Google maps API and R

September 3, 2013
By

(This article was first published on Jose Gonzalez » R, and kindly contributed to R-bloggers)

The White House

This post shows how to use Google Maps‘ API with R. Combine the first part with Plyr and it becomes a very powerful tool in just a few lines of code.

You can find a gist in RMarkdown with the code here or click below to continue reading.


#### This script uses RCurl and RJSONIO to download data from Google's API:
#### Latitude, longitude, location type (see explanation at the end), formatted address
#### Notice ther is a limit of 2,500 calls per day

library(RCurl)
library(RJSONIO)
library(plyr)

url <- function(address, return.call = "json", sensor = "false") {
 root <- "http://maps.google.com/maps/api/geocode/"
 u <- paste(root, return.call, "?address=", address, "&sensor=", sensor, sep = "")
 return(URLencode(u))
}

geoCode <- function(address,verbose=FALSE) {
 if(verbose) cat(address,"\n")
 u <- url(address)
 doc <- getURL(u)
 x <- fromJSON(doc,simplify = FALSE)
 if(x$status=="OK") {
 lat <- x$results[[1]]$geometry$location$lat
 lng <- x$results[[1]]$geometry$location$lng
 location_type <- x$results[[1]]$geometry$location_type
 formatted_address <- x$results[[1]]$formatted_address
 return(c(lat, lng, location_type, formatted_address))
 } else {
 return(c(NA,NA,NA, NA))
 }
}

##Test with a single address
#address <- geoCode("The White House, Washington, DC")
#address
#[1] "38.8976831"
#[2] "-77.0364972"
#[3] "APPROXIMATE"
#[4] "The White House, 1600 Pennsylvania Avenue Northwest, Washington, D.C., DC 20500, USA"

# Use plyr to getgeocoding for a vector
#address <- c("The White House, Washington, DC","The Capitol, Washington, DC")
#locations <- ldply(address, function(x) geoCode(x))
#names(locations) <- c("lat","lon","location_type", "forAddress")

#Location type, for more info check here: https://developers.google.com/maps/documentation/directions/
#"ROOFTOP" indicates that the returned result is a precise geocode for which we have location information accurate down to street address precision.
#RANGE_INTERPOLATED" indicates that the returned result reflects an approximation (usually on a road) interpolated between two precise points (such as intersections). Interpolated results are generally returned when rooftop geocodes are unavailable for a street address.
#GEOMETRIC_CENTER" indicates that the returned result is the geometric center of a result such as a polyline (for example, a street) or polygon (region).
#APPROXIMATE" indicates that the returned result is approximate.

The post Using Google maps API and R appeared first on Jose Gonzalez.

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