These are the base plots for ggplot2 cheatsheet.

Graphical Primitives – a, b

library(ggplot2)

a <- ggplot(economics, aes(date, unemploy))

b <- ggplot(seals, aes(x = long, y = lat))

One Variable – c, c2, d

c <- ggplot(mpg, aes(hwy))
c2 <- ggplot(mpg)

d <- ggplot(mpg, aes(fl))

Two Variables – e, f, g, h, i, df, j, data, map, k

e <- ggplot(mpg, aes(cty, hwy))

f <- ggplot(mpg, aes(class, hwy))

g <- ggplot(diamonds, aes(cut, color))

h <- ggplot(diamonds, aes(carat, price))

i <- ggplot(economics, aes(date, unemploy))

df <- data.frame(grp = c("A", "B"), fit = 4:5, se = 1:2)
j <- ggplot(df, aes(grp, fit, ymin = fit-se, ymax = fit+se))

install.packages('maps')
## Error in install.packages : Updating loaded packages
data <- data.frame(murder = USArrests$Murder, state = tolower(rownames(USArrests)))
map <- map_data("state")
k <- ggplot(data, aes(fill = murder))

Three Variables – seals$z, l

seals$z <- with(seals, sqrt(delta_long^2 + delta_lat^2))
l <- ggplot(seals, aes(long, lat))

Scales – n, o, p

n <- d + geom_bar(aes(fill = fl))

o <- c + geom_dotplot(aes(fill = ..x..))

p <- e + geom_point(aes(shape = fl, size = cyl))

Coordinate Systems – r

r <- d + geom_bar()

Position Adjustments – s

s <- ggplot(mpg, aes(fl, fill = drv))

Faceting – t

t <- ggplot(mpg, aes(cty, hwy)) + geom_point()