Stacked bar plot using factor lists in base R

Question

I am hoping to make a stacked bar plot to show two factors. The questions and answers I can find on this site that address this problem all work with data that appears to be in a matrix format and use ggplot2. My data is in lists of observations, like this:

mydata = data.frame(V1=c("A","B","B","C","C"), V2=c("X","X","Y","Z","Z"))

I would like to show categories of V1 on the x axis of my plot, but stacked to show the proportions of V2 in each bar.

I can use the "count" function in the plyr library to find the frequency of each observation,

library(plyr)
mydata.count = count(mydata)

but I don't know how to structure my barplot command to group data by the level of V1: barplot(mydata.count$freq) separates all combinations of V1 and V2 into separate bars.

If possible, I would like to create this plot using the base R barplot functions so that it is visually consistent with other plots in my study.

Answer 1

Use table to create a contingency table of the counts for all combinations of V1 and V2. Then, use barplot to create the stacked bar plot. When used with matrix, barplot creates stacked vertical bars where the columns appear on x-axis - so it may be necessary to transpose the data.

m = t(table(mydata))

colors = c("red", "green", "blue")
graphics.off()
windows(8, 6)
barplot(m, col = colors)
legend("topleft", legend = row.names(m), fill = colors)

Answer 2

Here is another possibility with ggplot:

ggplot(as.data.frame(table(mydata)), aes(x=V1, y=Freq, fill=V2)) + geom_bar(stat="identity")

ggplot(as.data.frame(table(mydata)), aes(x=V2, y=Freq, fill=V1)) + geom_bar(stat="identity")