Using Google Maps API: Mol Bubi Competition

A few friends and I are involved in the Budapest public bicycle data science competition. As of right now we are in the top ten, although in all honesty, it hasn’t really started yet. We signed a non-disclosure agreement, so I cannot really share any cool details. What I can share however, is the function I wrote in R to get calculate the distances and duration of bike trips using Google Maps’ API.

#distance calucations
#### This script uses RCurl and RJSONIO to download data from Google's API

library(RCurl)
library(RJSONIO)

#define api key as: api<-"YOURAPI"
#the function assumes address input in following dataframe:
#lat1,lng1,lat2,lng2

DistDur <- function(address,time = as.integer(Sys.time()),mode, return.call = "json", sensor = "false") {
  address1<-paste(address[,1],address[,2], sep=" ")
  address2<-paste(address[,3],address[,4], sep=" ")
  root <- "https://maps.googleapis.com/maps/api/directions/"
  u <- paste(root, return.call, "?origin=", address1, "&destination=",address2,"&departure_time=",time,"&mode=",mode,"&key=",api,sep = "")
  for (a in 1:length(u)){
    url<-URLencode(u[a])
    doc <- getURL(url)
    x <- fromJSON(doc,simplify = FALSE)
    dist<-0
    dura<-0
    for (i in 1:length(x$routes[[1]]$legs[[1]]$steps))
    {
      dist<-x$routes[[1]]$legs[[1]]$steps[[i]]$distance$value+dist
      dura<-x$routes[[1]]$legs[[1]]$steps[[i]]$duration$value+dura
    }
    address$dura[a]<-dura
    address$dist[a]<-dist
  }
  return(address)
}

The code itself is quite simple, but its my first time using the Google Maps API and I was amazed by how easy it was. This and more can be found on my Github.