If I have a data frame, such as:
group=rep(1:4,each=10)
data=c(seq(1,10,1),seq(5,50,5),seq(20,11,-1),seq(0.3,3,0.3))
DF=data.frame(group,data)
Now, I would like to divide each data element by the mean of its group. For example:
group=rep(1:4,each=10)
data=c(seq(1,10,1),seq(5,50,5),seq(20,11,-1),seq(0.3,3,0.3))
DF=data.frame(group,data)
aggregate(DF,by=list(DF$group),FUN=mean)
#Group.1 group data
#1 1 1 5.50
#2 2 2 27.50
#3 3 3 15.50
#4 4 4 1.65
data1=c(seq(1,10,1)/5.5,seq(5,50,5)/27.5,seq(20,11,-1)/15.5,seq(0.3,3,0.3)/1.65)
DF1=data.frame(group, data1)
However, this is a bit convoluted, and work not work easily in a large dataset. I feel like there is an apply application which could be used here, but I cannot find a nice way to do it.
Here's the usual set of options (thanks to @G.Grothendieck for simplification of ave):
# base R
DF$newdata = ave(DF$data, DF$group, FUN = function(x) x/mean(x))
# or...
DF$newdata = DF$data / ave(DF$data, DF$group)
# dplyr
library(dplyr)
DF %>% group_by(group) %>% mutate(newdata = data/mean(data))
# data.table
library(data.table)
setDT(DF)[, newdata := data/mean(data), by=group]