HI,
May be this helps:
set.seed(24)
dat1<-
data.frame(age=sample(30:70,120,replace=TRUE),income=sample(40000:80000,120,replace=FALSE),country=rep(c("USA","GB","France"),each=40),stringsAsFactors=FALSE)
library(plyr)
ldply(dlply(dat1,.(country),lm,formula=income~0+age),function(x) coef(x))
# country age
#1 France 1127.192
#2 GB 1194.586
#3 USA 1161.795
#or
do.call(rbind,lapply(split(dat1,dat1$country),function(x)
coef(with(x,lm(income~0+age)))))
# age
#France 1127.192
#GB 1194.586
#USA 1161.795
#or
do.call(rbind,lapply(unique(dat1$country),function(x) {subframe<-
dat1[which(dat1$country==x),]; fit<- lm(income~0+age,data=subframe);
Coef1<-data.frame(age=coef(fit)); row.names(Coef1)<-x; Coef1}))
# age
#USA 1161.795
#GB 1194.586
#France 1127.192
A.K.
----- Original Message -----
From: "CHEN, Cheng" <chench...@gmail.com>
To: R-help@r-project.org
Cc:
Sent: Sunday, May 19, 2013 8:31 AM
Subject: [R] How to run lm for each subset of the data frame,
and then aggreage the result?
Hi gurus,
I have a big data frame df, with columns named as :
age, income, country
what I want to do is very simpe actually, do
fitFunc<-function(thisCountry){
subframe<-df[which(country==thisCountry),];
fit<-lm(income~0+age, data=subframe);
return(coef(fit));}
for each individual country. Then aggregate the result into a new data
frame looks like :
countryname, coeffname1 USA 1.22 GB
1.03 France 1.1
I tried to do :
do.call("rbind", lapply(countries, fitFunc))
but this only gives something like:
age
[1,] 2.540879
[2,] 2.428830
[3,] 2.369560
How should I proceed?
can anyone help?
--
*CHEN*, Cheng
[[alternative HTML version deleted]]
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