Plot maps with ‘base’ mapping tools in R
Understanding what kind of data you have (polygons or points?) and what you want to map is pivotal to start your mapping.
- First you need a shapefile of the area you want to plot, such as metropolitan France. There are various resources where to get them from: DIVA-GIS and EUROSTAT are those that I use the most. It’s always important to have a .prj file included, as your final map ‘should’ be projecte. I say “should” as sometimes it is just not possible, especially if you work with historical maps.
- Upload libraries
Load and prepare data
setwd(paste(mypath))
fr.prj <- readOGR(".", "FRA_adm2")
## OGR data source with driver: ESRI Shapefile ## Source: ".", layer: "FRA_adm2" ## with 96 features ## It has 18 fields
## NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
map(fr.prj)
## Warning in SpatialPolygons2map(database, namefield = namefield): database ## does not (uniquely) contain the field 'name'.
head(fr.prj@data)
## ID_0 ISO NAME_0 ID_1 NAME_1 ID_2 NAME_2 VARNAME_2 ## 0 76 FRA France 989 Alsace 13755 Bas-Rhin Unterelsaá ## 1 76 FRA France 989 Alsace 13756 Haut-Rhin Oberelsaá ## 2 76 FRA France 990 Aquitaine 13757 Dordogne <NA> ## 3 76 FRA France 990 Aquitaine 13758 Gironde Bec-D'Ambes ## 4 76 FRA France 990 Aquitaine 13759 Landes Landas ## 5 76 FRA France 990 Aquitaine 13760 Lot-Et-Garonne <NA> ## NL_NAME_2 HASC_2 CC_2 TYPE_2 ENGTYPE_2 VALIDFR_2 VALIDTO_2 ## 0 <NA> FR.BR <NA> Département Department 17900226 Unknown ## 1 <NA> FR.HR <NA> Département Department 17900226 Unknown ## 2 <NA> FR.DD <NA> Département Department 17900226 Unknown ## 3 <NA> FR.GI <NA> Département Department 17900226 Unknown ## 4 <NA> FR.LD <NA> Département Department 17900226 Unknown ## 5 <NA> FR.LG <NA> Département Department 17900226 Unknown ## REMARKS_2 Shape_Leng Shape_Area ## 0 <NA> 4.538735 0.5840273 ## 1 <NA> 3.214178 0.4198797 ## 2 <NA> 5.012795 1.0389622 ## 3 <NA> 9.200047 1.1489822 ## 4 <NA> 5.531231 1.0372815 ## 5 <NA> 4.489830 0.6062017
# load or create data set.seed(100) myvar <- rnorm(1:96)
# manipulate data for the plot france.geodata <- data.frame(id=rownames(fr.prj@data), mapvariable=myvar) head(france.geodata)
## id mapvariable ## 1 0 1.12200636 ## 2 1 0.05912043 ## 3 2 -1.05873510 ## 4 3 -1.31513865 ## 5 4 0.32392954 ## 6 5 0.09152878
Use ggmap
# fortify prepares the shape data for ggplot france.dataframe <- fortify(fr.prj) # convert to data frame for ggplot
## Regions defined for each Polygons
head(france.dataframe)
## long lat order hole piece id group ## 1 7.847912 49.04728 1 FALSE 1 0 0.1 ## 2 7.844539 49.04495 2 FALSE 1 0 0.1 ## 3 7.852439 49.04510 3 FALSE 1 0 0.1 ## 4 7.854333 49.04419 4 FALSE 1 0 0.1 ## 5 7.855955 49.04431 5 FALSE 1 0 0.1 ## 6 7.856299 49.03776 6 FALSE 1 0 0.1
#now combine the values by id values in both dataframes france.dat <- join(france.geodata, france.dataframe, by="id") head(france.dat)
## id mapvariable long lat order hole piece group ## 1 0 1.122006 7.847912 49.04728 1 FALSE 1 0.1 ## 2 0 1.122006 7.844539 49.04495 2 FALSE 1 0.1 ## 3 0 1.122006 7.852439 49.04510 3 FALSE 1 0.1 ## 4 0 1.122006 7.854333 49.04419 4 FALSE 1 0.1 ## 5 0 1.122006 7.855955 49.04431 5 FALSE 1 0.1 ## 6 0 1.122006 7.856299 49.03776 6 FALSE 1 0.1
# Plot 3
p <- ggplot(data=france.dat, aes(x=long, y=lat, group=group))
p <- p + geom_polygon(aes(fill=mapvariable)) +
geom_path(color="white",size=0.1) +
coord_equal() +
scale_fill_gradient(low = "#ffffcc", high = "#ff4444") +
labs(title="Our map",fill="My variable")
# plot the map
p
Use plot basic
nclassint <- 5 #number of colors to be used in the palette cat <- classIntervals(myvar, nclassint,style = "jenks") #style refers to how the breaks are created colpal <- brewer.pal(nclassint,"RdBu") color <- findColours(cat,rev(colpal)) #sequential bins <- cat$brks lb <- length(bins)
plot(fr.prj, col=color,border=T)
legend("bottomleft",fill=rev(colpal),legend=paste(round(bins[-length(bins)],1),":",round(bins[-1],1)),cex=1, bg="white")
