######
# data on price indices of real estate in France
data(immob)
row.names(immob)<-immob$Nom
# immob is a data.frame object. We have to create
# a Spatial object, by using first the longitude and latitude
# to create Spatial Points object ...
immob.sp = SpatialPoints(cbind(immob$longitude,immob$latitude))
# ... and then by integrating other variables to create SpatialPointsDataFrame
immob.spdf = SpatialPointsDataFrame(immob.sp, immob)
# For more details, see vignette('sp', package="sp")
# optional : we add some contours that don't correspond to the spatial unit
# but are nice for mapping
require("maptools")
midiP <- readShapePoly(system.file("shapes/region.shp", package="GeoXp")[1])
cont_midiP<-spdf2list(midiP[-c(22,23),])$poly
# A basic call of dblehistomap function
dblehistomap(immob.spdf,c("prix.vente","prix.location"),
carte= cont_midiP, identify=TRUE, cex.lab=0.6)
###
# data colombus
x <- readShapePoly(system.file("shapes/columbus.shp", package="maptools")[1])
# example of use with many options
dblehistomap(x,c("HOVAL","CRIME"), nbcol=c(5,10),type="percent",
xlab=c("hoval","crime"),identify=TRUE, cex.lab=0.7, ylab=c("percent","percent"),
col=c("pink","orange"),pch=14,axes=TRUE)
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