R/ggplot2 aggregation function using multiple columns

Question

I would like to ggplot(R) a bar graph of aggregated values based on the computation of multiple numeric columns of a table vs. some categorical column (this is also the "group by") of said table.

Table:

V1 V2 categorical 3 4 c1 5 6 c2 7 3 c2 3 8 c3

I would like to do something like this:

ggplot(Table, aes(categorical)) + stat_summary_bin(aes="V1 * V2"), fun.y = function(r) r$V1 * r$V2)

where the function stuffed into fun.y accepts a row and then accesses its corresponding V1 and V2 values to return what would be mapped to the y-axis. The desired result would be a plot of 3 bars where c1: 12, c2: 51, and c3: 24.

Answer 1

As long as you just want to add the results from each row, geom_bar with position = "stack" will do just fine. aes() is very liberal about what you can pass to it in terms of functions of columns.

ggplot(df, aes(x = categorical, y = V1 * V2)) +
    geom_bar(stat = "identity", position = "stack")

Answer 2

Alternatively to work with stat_summary_bin , you can specify the fun.y parameter as sum :

ggplot(df, aes(x = categorical)) +
    stat_summary_bin(aes(y = V1 * V2), fun.y = "sum", geom = "bar")