library(ggplot2)
data("mtcars")
str(mtcars)
## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
I heartily recommend: http://www.cookbook-r.com/
g0 <- ggplot( data = mtcars,
aes(y = mpg, x = as.factor(gear))
) +
geom_boxplot()
g0
Notice I’ve forced gear to be a factor
g1 <- ggplot( data = mtcars, aes(y = mpg, x = as.factor(gear))) +
geom_point( aes(colour = as.factor(carb)))
g1
g2 <- ggplot( data = mtcars, aes(y = mpg, x = as.factor(gear))) +
geom_point( aes(colour = carb, jitter = 4))
g2
g3 <- ggplot( data = mtcars, aes(y = mpg, x = as.factor(gear))) +
geom_point(aes(colour = as.factor(carb), size = wt))
g3
g4 <- ggplot( data = mtcars, aes(y = mpg, x = as.factor(gear))) +
geom_jitter(position = position_jitter(),aes(colour = as.factor(carb), size = wt))
g4
g5 <- ggplot( data = mtcars, aes(y = mpg, x = as.factor(gear))) +
geom_point(aes(colour = as.factor(carb), size = wt)) +
ggtitle("Red Main Title") +
ylab("Miles Per Gallon") + xlab("Number of Gears") +
theme(
plot.title = element_text(lineheight=.8, face="bold", size = 25, colour = "Red"),
axis.title.x = element_text(face="bold", size = 25, colour = "#FF0055") ,
axis.title.y = element_text(face="bold", size = 15) ,
axis.text.x = element_text(face="bold", size = 15, colour = "Red") ,
axis.text.y = element_text(face="bold", size = 15)
) +
geom_hline(aes(yintercept=mean(mpg)), colour="#990000", linetype="dashed", size = 2, alpha = 0.3)
g5