I have three factors (set1, set2, and set3) for each of about 50 individuals. The values for set1, set2, and set3 are "A","B","C". I'd like to make a heatmap-like plot of these data but have the legend show the color associated with the values (eg., A='red', B='blue', C='black'). Any suggestions?
Thanks.
If we want to see how categorical variables interact with each other, heatmaps are a very useful way to do so. While you can use a heatmap to visualize the relationship between any two categorical variables, it's quite common to use heatmaps across dimensions of time.
Mosaic plots are good for comaparing two categorical variables, particularly if you have a natural sorting or want to sort by size.
Bar Charts and Pie Charts are used to visualize categorical data.
Frequency tables, pie charts, and bar charts are the most appropriate graphical displays for categorical variables.
I decided it would be easist to approach this with ggplot2 (for me anyway):
#recreate a data set
dat <- data.frame(person=factor(paste0("id#", 1:50),
levels =rev(paste0("id#", 1:50))), matrix(sample(LETTERS[1:3], 150, T), ncol = 3))
library(ggplot2); library(reshape2)
dat3 <- melt(dat, id.var = 'person')
ggplot(dat3, aes(variable, person)) + geom_tile(aes(fill = value),
colour = "white") + scale_fill_manual(values=c("red", "blue", "black"))
A similar plot can also be made with base graphics. Here is one method using the base image
function. This sample has a categorical response rather than a numeric one.
dx <- data.frame( Tasks = c('1','2','3','4'),
Phase1 = c('Done','Done','Done','WIP'),
Phase2 = c('WIP','Done','Done',''),
Phase3 = c('','WIP','Done',''))
ff<-factor(as.matrix(dx[,2:4]),
levels=c("Done","WIP",""),
labels=c("done","wip","-empty-")
)
fx<-matrix(as.numeric(ff), ncol=ncol(dx)-1)
#use labels to assign colors
col<-c(done="darkgreen",wip="orange","-empty-"="black")
imgflip<-function(x) {t(x[nrow(x):1,])}
image(imgflip(fx),
breaks=(1:(nlevels(ff)+1))-.5,
col=col[levels(ff)],
xaxt="n", yaxt="n"
)
axis(2, at=seq(0,1,length.out=nrow(dx)), labels=rev(paste("Task",dx$Tasks)), las=2)
axis(3, at=seq(0,1,length.out=length(names(dx))-1), labels=names(dx)[-1])
which will produce this picture.
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