Solución:
Utilizando el rworldmap
paquete, puede utilizar lo siguiente:
library(rworldmap)
theCountries <- c("DEU", "COD", "BFA")
# These are the ISO3 names of the countries you'd like to plot in red
malDF <- data.frame(country = c("DEU", "COD", "BFA"),
malaria = c(1, 1, 1))
# malDF is a data.frame with the ISO3 country names plus a variable to
# merge to the map data
malMap <- joinCountryData2Map(malDF, joinCode = "ISO3",
nameJoinColumn = "country")
# This will join your malDF data.frame to the country map data
mapCountryData(malMap, nameColumnToPlot="malaria", catMethod = "categorical",
missingCountryCol = gray(.8))
# And this will plot it, with the trick that the color palette's first
# color is red
EDITAR: agregue otros colores e incluya una imagen
## Create multiple color codes, with Burkina Faso in its own group
malDF <- data.frame(country = c("DEU", "COD", "BFA"),
malaria = c(1, 1, 2))
## Re-merge
malMap <- joinCountryData2Map(malDF, joinCode = "ISO3",
nameJoinColumn = "country")
## Specify the colourPalette argument
mapCountryData(malMap, nameColumnToPlot="malaria", catMethod = "categorical",
missingCountryCol = gray(.8), colourPalette = c("red", "blue"))
Intente usar el paquete googleVis y use las funciones gvisGeoMap
p.ej
G1 <- gvisGeoMap(Exports,locationvar="Country",numvar="Profit",options=list(dataMode="regions"))
plot(G1)
library(maptools)
data(wrld_simpl)
myCountries = [email protected]$NAME %in% c("Australia", "United Kingdom", "Germany", "United States", "Sweden", "Netherlands", "New Zealand")
plot(wrld_simpl, col = c(gray(.80), "red")[myCountries+1])
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