install.packages("rworldmap") 
library(rworldmap)
data(countryExData)
country2Region(regionType="Stern") 
sternEnvHealth<-country2Region(inFile=countryExData, nameDataColumn="ENVHEALTH",joinCode="ISO3", nameJoinColumn="ISO3V10",regionType="Stern",FUN="mean")
sPDF<-joinCountryData2Map(countryExData,joinCode = "ISO3",nameJoinColumn="ISO3V10")
mapCountryData(sPDF, nameColumnToPlot="BIODIVERSITY", mapTitle="World Biodiversity", oceanCol="lightblue", missingCountryCol="white", borderCol="black")
######
mapCountryData(sPDF,nameColumnToPlot="BIODIVERSITY", mapTitle="Asia",oceanCol="lightblue",missingCountryCol="white", mapRegion="Asia",borderCol="black")
######
mapCountryData(sPDF,nameColumnToPlot="BIODIVERSITY", mapTitle="Australia",oceanCol="lightblue",missingCountryCol="white", xlim=c(110,160), ylim=c(-48,-5),borderCol="black")


# mapBubbles(dF=getMap())
mapBubbles(dF=getMap(),oceanCol="lightblue",landCol="wheat")
head(getMap()$NAME)

mammals<- read.table(text="
Country   'Mammal species' 'threatened spp'   Lat  Lon
Canada	426	40	 60 -95
Brazil   648  80   -34  -64
Mexico	923	96   24 -102
Peru	     647	63  -9   -75
Colombia 442	58	3.9	-73
'United States' 440 40 39 -99
Argentina	374	38    -35  -65
Ecuador 372 47  -1 -78
Bolivia 362 21 -17  -64
Chile 143 19  -37 -72
", header=TRUE) 

mapBubbles(dF=mammals, nameZSize="Mammal.species",nameZColour="Country",oceanCol="lightblue", landCol="wheat",nameX = "Lat", nameY = "Lon", main="Number of Mammal species",symbolSize=0.5)