R log-transformation on dataframe - r

Question

I have a dataframe (df) with the values (V) of different stocks at different dates (t). I would like to get a new df with the profitability for each time period.
Profitability is: ln(Vi_t / Vi_t-1)
where:
ln is the natural logarithm
Vi_t is the Value of the stock i at the date t
Vi_t-1 the value of the same stock at the date before
This is the output of df[1:3, 1:10]
date SMI Bond ABB ADDECO Credit Holcim Nestle Novartis Roche
1 01/08/88 1507.5 3.63 4.98 159.20 15.62 14.64 4.01 4.59 11.33
2 01/09/88 1467.4 3.69 4.97 161.55 15.69 14.40 4.06 4.87 11.05
3 01/10/88 1538.0 3.27 5.47 173.72 16.02 14.72 4.14 5.05 11.94
Specifically, instead of 1467.4 at [2, "SMI"] I want the profitability which is ln(1467.4/1507.5) and the same for all the rest of the values in the dataframe.
As I am new to R I am stuck. I was thinking of using something like mapply, and create the transformation function myself.
Any help is highly appreciated.

Answer 1

This will compute the profitabilities (assuming data is in a data.frame call d):
(d2<- log(embed(as.matrix(d[,-1]), 2) / d[-dim(d)[1], -1]))
# SMI Bond ABB ADDECO Credit Holcim Nestle Novartis Roche
#1 -0.02696052 0.01639381 -0.002010051 0.01465342 0.004471422 -0.01652930 0.01239173 0.05921391 -0.02502365
#2 0.04699074 -0.12083647 0.095858776 0.07263012 0.020814375 0.02197891 0.01951281 0.03629431 0.07746368
Then, you can add in the dates, if you want:
d2$date <- d$date[-1]
Alternatively, you could use an apply based approach:
(d2 <- apply(d[-1], 2, function(x) diff(log(x))))
# SMI Bond ABB ADDECO Credit Holcim Nestle Novartis Roche
#[1,] -0.02696052 0.01639381 -0.002010051 0.01465342 0.004471422 -0.01652930 0.01239173 0.05921391 -0.02502365
#[2,] 0.04699074 -0.12083647 0.095858776 0.07263012 0.020814375 0.02197891 0.01951281 0.03629431 0.07746368