How do I find the difference between two values in different dataframes across multiple rows and columns?

Question

I have two dataframes:

df1:

WAV    UV     VIOLET    BLUE
sD1    10.8   10.1      23.5
sA4    6.2    8.2       19.9
sA1    8.3    11.7      28.6
sC2    7.9    8.2       31.0
sC3    10.7   9.5       18.1

df2:

ID    UV     VIOLET    BLUE
D1    7.9    10.1      19.3
D2    7.0    9.2       15.9
D3    21.4   20.7      27.4
D4    10.3   8.9       20.9
D5    21.7   16.5      21.3

I want to find the difference between the sum of the columns of D1 in df2 and the columns of each row in df1 and produce this output in a new dataframe. Then, this needs to be repeated for D2 of df2 with every row of df1 and so on. Each new difference between the sums for each row should be a separate entry of the new dataframe and each list of the differences row of df2 should be a new row in the output. So the output should look like this:

D1    sum(D1)-sum(sD1)  sum(D1)-sum(sA4)  sum(D1)-sum(sA1)  sum(D1-sC2)  sum(D1)-sum(sC3)
D2    sum(D2)-sum(sD1)  sum(D2)-sum(sA4)  sum(D2)-sum(sA1)  sum(D2-sC2)  sum(D2)-sum(sC3)
D3    sum(D3)-sum(sD1)  sum(D3)-sum(sA4)  sum(D3)-sum(sA1)  sum(D3-sC2)  sum(D3)-sum(sC3)
D4    sum(D4)-sum(sD1)  sum(D4)-sum(sA4)  sum(D4)-sum(sA1)  sum(D4-sC2)  sum(D4)-sum(sC3)
D5    sum(D5)-sum(sD1)  sum(D5)-sum(sA4)  sum(D5)-sum(sA1)  sum(D5-sC2)  sum(D5)-sum(sC3)

I'm open to any suggestions.

Answer 1

Here are three ways, two of which have already been mentioned by @Onyambu in comment. Of these, the outer option seems to be the fastest.

outer(rowSums(df1[,-1]), rowSums(df2[,-1]), "-")

or

sapply(rowSums(df1[-1]),"-",rowSums(df2[-1]))

or

sapply(rowSums(df1[,-1]), function(x) x - rowSums(df2[,-1]))

So for instance, you can do:

df <- data.frame(outer(rowSums(df1[,-1]), rowSums(df2[,-1]), "-"))
colnames(df) <- df1$WAV
rownames(df) <- df2$ID