It's not clear what you mean by wanting the "corresponding values of the other column". The first part is easy to accomplish using the g (# of groups) argument:
dfrm$Agrp <- cut2(dfrm$A, g=trunc(length(dfrm$A)/25) )
You can aggregate means or medians of B within Agrp's using tapply
or ave
or one of the Hmisc summary functions. There are several worked examples in one of today's questions: How to get Summary statistics by group as well as many other examples of using those functions or aggregate
or the pkg:plyr functions.
Given that the number of B values will not necessarily be constant across groups the only way I can think to deliver the individual values by A-grouped-value would be with split
. I added an extra row to illustrate that a non-even split might need to return a list rather than a more "rectangular" object :
dat <- read.table(text="A B
-10.834510 1.680173
11.012966 1.866603
-16.491415 1.868667
-14.485036 1.900002
2.629104 1.960929
-3.597291 2.005348\n 3.5943 3.796", header=TRUE)
dat$Agrp <- cut2(dat$A, g=trunc(length(dat$A)/3) )
split(dat$B, dat$Agrp)
#-----
$`[-16.49, 2.63)`
[1] 1.680173 1.868667 1.900002 2.005348
$`[ 2.63,11.01]`
[1] 1.866603 1.960929 3.796000
If you want the vector of values on which the splits were done then that can be accomplished by using regex on levels(dat$Agrp)
.