denmarkggmapggplot2r
I have installed the following two packages:
library(ggmap)
library(maps)
I have found code online to create a world map (see below).
How do I zoom the plot on a country level?
For example, Denmark.
ggplot()+
borders("world", colour="gray50", fill="gray50")
You first need to import the CSV file with v.in.ascii to create a vector points map. Add a new column "Country" of varchar(25) with v.db.addcol. Then simply populate the new column with v.what.vect (see also example in that manual page).
Robin Lovelace has provided a nice little function to download a ggmap object and convert it to a raster. Using this you could do:
library(ggmap)
library(raster)
library(rgdal)
# courtesy R Lovelace
ggmap_rast <- function(map){
map_bbox <- attr(map, 'bb')
.extent <- extent(as.numeric(map_bbox[c(2,4,1,3)]))
my_map <- raster(.extent, nrow= nrow(map), ncol = ncol(map))
rgb_cols <- setNames(as.data.frame(t(col2rgb(map))), c('red','green','blue'))
red <- my_map
values(red) <- rgb_cols[['red']]
green <- my_map
values(green) <- rgb_cols[['green']]
blue <- my_map
values(blue) <- rgb_cols[['blue']]
stack(red,green,blue)
}
dc <- get_map(location = 'DC', zoom = 12)
dc.rast <- ggmap_rast(map = dc) # convert google map to raster object
nhbds <- readOGR("Census_Tracts_-_2010", "Census_Tracts_-_2010") # use rgdal to preserve projection
dc.only <- mask(dc.rast, nhbds) # clip to bounds of census tracts
# prep raster as a data frame for printing with ggplot
dc.df <- data.frame(rasterToPoints(dc.only))
ggplot(dc.df) +
geom_point(aes(x=x, y=y, col=rgb(layer.1/255, layer.2/255, layer.3/255))) +
scale_color_identity()
Best Answer
If we look at
?bordersand, for more into,?map, we see that we may use theregionsargument: