I have made this short code to automate geocoding of IP addresses by using the freegeoip.net (15,000 queries per hour by default; excellent service!):
> library(RCurl)
Loading required package: bitops
> ip.lst =
c("193.198.38.10","91.93.52.105","134.76.194.180","46.183.103.8")
> q = do.call(rbind, lapply(ip.lst, function(x){
try( data.frame(t(strsplit(getURI(paste0("freegeoip.net/csv/", x)), ",")[[1]]), stringsAsFactors = FALSE) )
}))
> names(q) = c("ip","country_code","country_name","region_code","region_name","city","zip_code","time_zone","latitude","longitude","metro_code")
> str(q)
'data.frame': 4 obs. of 11 variables:
$ ip : chr "193.198.38.10" "91.93.52.105" "134.76.194.180" "46.183.103.8"
$ country_code: chr "HR" "TR" "DE" "DE"
$ country_name: chr "Croatia" "Turkey" "Germany" "Germany"
$ region_code : chr "" "06" "NI" ""
$ region_name : chr "" "Ankara" "Lower Saxony" ""
$ city : chr "" "Ankara" "Gottingen" ""
$ zip_code : chr "" "06450" "37079" ""
$ time_zone : chr "Europe/Zagreb" "Europe/Istanbul" "Europe/Berlin" ""
$ latitude : chr "45.1667" "39.9230" "51.5333" "51.2993"
$ longitude : chr "15.5000" "32.8378" "9.9333" "9.4910"
$ metro_code : chr "0\r\n" "0\r\n" "0\r\n" "0\r\n"
In three lines of code you get coordinates for all IPs including city/country codes. I wonder if this could be parallelized so it runs even faster? To geocode >10,000 IPs can take hours otherwise.