Format the ggplot2 map

ggplot2, maps, plot, r

Solution

In regard to changing the colorscale, ggplot2 has a uniform way of handling scales. The function you are looking for always has the format `scale_{which_scale}_{scale_type}`, where `which_scale` is an aesthetic (what you use in `aes()`, for example `fill` or `size`), and `scale_type` can be continuous or discrete, etc. What you are looking for if you want to tweak the `fill` scale is `scale_fill_continuous`, `scale_fill_gradient`, or `scale_fill_gradient2`. Have a look at the documentation of those functions.

A code example:

m2 <- m1 + geom_polygon(aes(x=long, y=lat, group=group, fill=rendapc))
m2 + scale_fill_gradient(low = "blue", high = "red")

Problem

I´m trying to produce a worldmap using ggplot2 in R. I want to show GDP per capita from Brazilian States. There are 2 problems: In the center of Country have two labels aren't easy to read the information. They are overlapping.Reducing the numbers not resolved. I would like to change the colour breaks and don't know how to access it. I would like to use colors to become easy to note the diferences of GDP. My data is: https://docs.google.com/file/d/0B_coFit6AovfcEFkbHBjZEJaQ1E/edit Here is my code: ``` library(maptools) gpclibPermit() library(ggplot2) library(rgdal) library(rgeos) library(ggmap) # read administrative boundaries (change folder appropriately) brMap <- readShapePoly("BRASIL.shp") brMap # read downloaded data (change folder appropriately) brRen <- read.csv("Renda.csv", sep = ";", quote = "\"", dec=".", stringsAsFactors = FALSE) brRen$rendapc <- as.numeric(as.character(brRen$rendapc)) # format as numeric #convert shp to UTF8 library(descr) brMap$ESTADO<-toUTF8(brMap$ESTADO, "IBM850") # convert shp data to data frame for ggplot as.data.frame(brMap) # para definir a region brMap = gBuffer(brMap, width=0, byid=TRUE) #correct problem with Polygons - TopologyException brMapDf <- fortify(brMap, region="UF") brMapDf # merge map and data brRenMapDf <- merge(brMapDf, brRen, by.x="id", by.y="Iden") brRenMapDf <- brRenMapDf[order(brRenMapDf$order),] # limit data to main Europe brazil.limits <- geocode(c("Monte Caburaí", "Barra do Chuí", "Serra do Divisor", "Ilhas Martin Vaz")) brRenMapDf <- subset(brRenMapDf, long > min(brazil.limits$lon) & long < max(brazil.limits$lon) & lat > min(brazil.limits$lat) & lat < max(brazil.limits$lat)) # ggplot mapping # data layer m0 <- ggplot(data=brRenMapDf) # empty map (only borders) m1 <- m0 + geom_path(aes(x=long, y=lat, group=group), color='gray') + coord_equal() m1 # fill with education expenditure data m2 <- m1 + geom_polygon(aes(x=long, y=lat, group=group, fill=rendapc)) m2 # inverse order (to have visible borders) m0 <- ggplot(data=brRenMapDf) m1 <- m0 + geom_polygon(aes(x=long, y=lat, group=group, fill=rendapc)) + coord_equal() m2 <- m1 + geom_path(aes(x=long, y=lat, group=group), color='black') m2 # over a GoogleMap (not working if not correctly projected) map <- get_map(location = 'Brazil', zoom=4) m0 <- ggmap(map) m1 <- m0 + geom_polygon(aes(x=long, y=lat, group=group, fill=rendapc), data=brRenMapDf, alpha=.9) m2 <- m1 + geom_path(aes(x=long, y=lat, group=group), data=brRenMapDf, color='black') m2 # add text library(doBy) txtVal <- summaryBy(long + lat + rendapc ~ id, data=brRenMapDf, FUN=mean, keep.names=T) m3 <- m2 + geom_text(aes(x=long, y=lat, label=rendapc), data=txtVal, col="yellow", hjust=0.5, vjust=0.5, cex=3) m3 ``` My result I want to improve:

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