just mess it all up. I could, of course, reintroduce
the date columns for the issue at hand, and do an intersect.
Best wishes,
Murali
From: Erik Iverson [EMAIL PROTECTED]
To: Murali Menon [EMAIL PROTECTED]
CC: r-help@stat.math.ethz.ch
Subject: Re: [R] Computing stats on common parts of multiple
Folks,
I have three dataframes storing some information about
two currency pairs, as follows:
R a
EUR-USD NOK-SEK
1.231.33
1.221.43
1.261.42
1.241.50
1.211.36
1.261.60
1.291.44
1.251.36
1.271.39
1.231.48
1.221.26
1.241.29
1.271.57
1.21
Murali -
I've come up with something that might with work, with gratutious use of
the *apply functions. See ?apply, ?lappy, and ?mapply for how this
would work. Basically, just set my.list equal to a list of data.frames
you would like included. I made this to work with matrices first, so
Suppose our data frames are called DF1, DF2 and DF3. Then
find the least number of rows, n, among them. Create a
list, DFs, of the last n rows of the data frames and another
list, mats, which is the same but in which each component is a
matrix. Create a parallel median function, pmedian,
Sorry, I switched variable names part way through. Here it is again:
DFs - list(DF1, DF2, DF3)
n - min(sapply(DFs, nrow))
DFs - lapply(DFs, tail, n)
mats - lapply(DFs, as.matrix)
pmedian - function(...) median(c(...))
medians - do.call(mapply, c(pmedian, mats))
replace(DFs[[1]], TRUE, medians)
