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This post shows how to produce a plot involving three categorical variables and one continuous variable using ggplot2
in R.
The following code is also available as a gist on github.
1. Create Data
First, let’s load ggplot2
and create some data to work with:
library(ggplot2) set.seed(4444) Data <- expand.grid(group=c("Apples", "Bananas", "Carrots", "Durians", "Eggplants"), year=c("2000", "2001", "2002"), quality=c("Grade A", "Grade B", "Grade C", "Grade D", "Grade E")) Group.Weight <- data.frame( group=c("Apples", "Bananas", "Carrots", "Durians", "Eggplants"), group.weight=c(1,1,-1,0.5, 0)) Quality.Weight <- data.frame( quality=c("Grade A", "Grade B", "Grade C", "Grade D", "Grade E"), quality.weight = c(1,0.5,0,-0.5,-1)) Data <- merge(Data, Group.Weight) Data <- merge(Data, Quality.Weight) Data$score <- Data$group.weight + Data$quality.weight + rnorm(nrow(Data), 0, 0.2) Data$proportion.tasty <- exp(Data$score)/(1 + exp(Data$score))
2. Produce Plot
And here’s the code to produce the plot.
ggplot(data=Data, aes(x=factor(year), y=proportion.tasty, group=group, shape=group, color=group)) + geom_line() + geom_point() + opts(title = "Proportion Tasty by Year, Quality, and Group") + scale_x_discrete("Year") + scale_y_continuous("Proportion Tasty") + facet_grid(.~quality )
And here’s what it looks like:
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