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Here is a little code snippet that shows how to do two things

1. Use the Google Maps API to resolve place names into lat-long coordinate pairs.
2. Plot R dataframes that contain lat-long data (for example from #1) onto Google Maps for quick visualization using the googleVis package.  The embedded map looks a little wonky here but it looks perfectly normal when you plot it locally in your browser. (Note: you need an internet connection for these maps to plot properly).
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Data: plotData • Chart ID: MapID71b85742e7
```require(XML)

getDocNodeVal=function(doc, path)
{
sapply(getNodeSet(doc, path), function(el) xmlValue(el))
}

gGeoCode=function(str)
{
library(XML)
doc = xmlTreeParse(u, useInternal=TRUE)
str=gsub(' ','%20',str)
lat=getDocNodeVal(doc, "/GeocodeResponse/result/geometry/location/lat")
lng=getDocNodeVal(doc, "/GeocodeResponse/result/geometry/location/lng")
list(lat = lat, lng = lng)
}

#### End functions borrowed from http://statisfaction.wordpress.com/2011/10/05/calling-google-maps-api-from-r/

# get some names of paleoanthropological sites in France.
placeNames<-c("Cro Magnon","La Ferrassie","Chauvet Cave","La Chapelle aux Saints", "Le Moustier")

#resolve the placenames into latlong
latLong<-lapply(placeNames, FUN=gGeoCode)

#format the latlong coordinates into the proper format lat:long
latLongFormatted<-lapply(latLong,FUN=function(x){
paste(x\$lat[1],x\$lng[1],sep=":")
})

#create a dataframe, formatting the place name string first and making the latlong a vector, not list
plotData<-data.frame(name=placeNames,latlong=unlist(latLongFormatted))

sites<-gvisMap(plotData,locationvar="latlong",tipvar="name", options=list(mapType='normal'))
plot(sites)```