Reputation: 36146
I'm looking for a way of simplifying the code bellow; I have 9 different measures that I'd like to plot against quality and am trying to avoid coping and pasting the code 9 times (or even having to write a function to plot and call the function 9 times):
p1<- ggplot(aes(x=quality, y = alcohol), data = df) + geom_boxplot()+ stat_summary(fun.y=mean,geom = 'point', shape = 4)
p2<- ggplot(aes(x=quality, y = pH), data = df) + geom_boxplot()+ stat_summary(fun.y=mean,geom = 'point', shape = 4)
grid.arrange(p1,p2, ncol=1)
anything that can be done there?
Thanks, Diego
Upvotes: 0
Views: 119
Reputation: 13139
Using do.call on a list of plots generated by plyr on a melted dataframe. (I'm assuming there is a reason you do not want to use facet_grid on melted data)
#generate some data
data <- data.frame(id=1:500, quality=sample(3:10,replace=TRUE,size=500))
for(i in 1:9){
data[,paste0("outcome_",i)]<-rnorm(500)
}
#melt it
melt_data <- melt(data,id.vars=c("id","quality"))
head(melt_data)
library(ggplot2)
library(gridExtra)
#generate a list of plots
plots <- dlply(melt_data,.(variable),function(chunk){
ggplot(data=chunk, aes(x=factor(quality), y = value)) + geom_boxplot()+
stat_summary(fun.y=mean,geom = 'point', shape = 4) +
#label y axis correctly
labs(y=unique(chunk$variable)
)
})
do.call(grid.arrange,c(plots,ncol=2))
Upvotes: 1
Reputation: 70643
You can use do.call
.
library(ggplot2)
p1 <- ggplot(airquality, aes(x = Ozone, y = Solar.R)) +
theme_bw() +
geom_point()
out <- list(p1, p1)
library(gridExtra)
do.call("grid.arrange", out)
Upvotes: 0