How to create legend (continuous colourbar) based on specific range of values in R/ggplot2? - r

Question

I have a dataframe named myKrige_new contains some latitude-longutude wise interpolated values. You can download from HERE. I have plotted this values on a particular area of a country map using ggplot2 package in R and I got this plot
But I want the legend(colourbar) of my plot would be like the following legend.
In my dataset here, the range of the data (pred) is 72 to 257. But I want my legend would show the value 0 to 200 because of comparing reason with other plot though there no value under 72 here .
So, I want to use 20 different colour like above legend that means last box of legend would contain colour regarding value greater than 200. I have used scale_fill_gradientn function but it didn't work. I have spend days to find some option to do it in R, didn't get success. Any kind of help will be highly appreciable.
R code :
library(scales)
library(ggplot2)
myKrige_new <- read.csv ("myKrige_new.csv")
range(myKrige_new$LON)
range(myKrige_new$LAT)
#Original skorea data transformed the same was as myKrige_new
skorea1 <- getData("GADM", country= "KOR", level=1)
skorea1 <- fortify(skorea1)
myKorea1 <- data.frame(skorea1)
###############
ggplot()+
theme_minimal() +
#SOLUTION 1:
#geom_tile(data = myKrige_new, aes(x= LON, y= LAT, fill = pred)) +
#SOLUTION 2: Uncomment the line(s) below:
#geom_point(data = myKrige_new, aes(x= LON, y= LAT, fill = pred),
#shape=22, size=8, colour=NA)+
#Solution 3
stat_summary_2d(data=myKrige_new, aes(x = LON, y = LAT, z = pred),bins = 30,
binwidth = c(0.05,0.05)) +
scale_fill_gradientn(colours=c("white","blue","green","yellow","red"),
values=rescale(c(0,50,100,150,200)),
guide="colorbar", name = "PM10 Conc")+
geom_map(data= myKorea1, map= myKorea1, aes(x=long,y=lat,map_id=id,group=group),
fill=NA, colour="black") +
coord_cartesian(xlim= c(126.6, 127.2), ylim= c(37.2 ,37.7)) +
labs(title= "PM10 Concentration in Seoul Area at South Korea",
x="", y= "")+
theme(legend.position = "bottom")+
guides(fill = guide_colourbar(barwidth = 27, barheight = NULL,
title.position = "bottom", title.hjust = 0.5))

Answer 1

Here is a working solution:
library(scales)
library(ggplot2)
library(raster) # needed for the `getData` function
library(dplyr) # needed for the `mutate` funtion
myKrige_new <- read.csv("~/Downloads/myKrige_new.csv")[-1]
range(myKrige_new$LON)
range(myKrige_new$LAT)
# Original skorea data transformed the same was as myKrige_new
skorea1 <- getData("GADM", country= "KOR", level=1)
skorea1 <- fortify(skorea1)
myKorea1 <- data.frame(skorea1)
# the range of pred goes above 200 (max = 257)
summary(myKrige_new$pred)
ggplot() +
theme_minimal() +
stat_summary_2d(data = mutate(myKrige_new,
pred = ifelse(pred > 200, 200, pred)),
aes(x = LON, y = LAT, z = pred),
bins = 30,
binwidth = c(0.05,0.05)) +
scale_fill_gradientn(colours=c("white","blue","green","yellow","red"),
values=rescale(c(0,50,100,150,200)),
name = expression(paste(PM[10], group("[",paste(mu,g/m^3), "]"))),
limits = c(0,200),
breaks = seq(0,200, 20),
guide = guide_colorbar(nbin = 20,
barwidth = 27,
title.position = "bottom",
title.hjust = 0.5,
raster = FALSE,
ticks = FALSE)) +
geom_map(data= myKorea1,
map= myKorea1,
aes(x=long,y=lat,map_id=id,group=group),
fill=NA,
colour="black") +
coord_equal(xlim= c(126.6, 127.2),
ylim= c(37.2 ,37.7)) +
scale_y_continuous(expand = c(0,0)) +
scale_x_continuous(expand = c(0,0)) +
labs(title = "PM10 Concentration in Seoul Area at South Korea",
x = "",
y = "") +
theme(legend.position = "bottom")
I added limits = c(0,200) and breaks = seq(0, 200, 20) to scale_fill_gradientn as well as nbin = 20 to guide_colorbar, this last change is optional because the default nbin is 20, but in your case you actually need 20. Also, adding limits means values outside the range are plotted in grey50 so I had to transform pred values above 200 to 200 to avoid that; the interpretation of red color is now 200+.
One more thing, the option raster in guide_colorbar changes the colorbar from a raster object to a set of rectangles achieving the look you were looking for.
Finally, I changed the coordinate system from cartesian to equal because you are plotting a map.
Here is the result hope it helps:
Update: added a expand argument to scale_y_continuous and scale_x_continuous as requested by OP