Depending upon what you are trying to do with them, how about storing the
dataframes as a multidimensional array of size 4x3x3 in the case below. After
that you can use the sapply function with the
appropriate MARGIN argument specified:
For example
mydfs <- as.array(list(df1, df2, df3))
sapply(X=mydfs, MARGIN=c(1,2), FUN=mean)
[,1] [,2] [,3]
V1 0.8206239 -0.51637848 -0.9025252
V2 -0.2828919 0.41837384 -0.4042646
V3 -0.8996891 -0.06284681 -0.2459261
--Mark Lamias
________________________________
From: Kaiyin Zhong <kindlych...@gmail.com>
To: r-help <r-help@r-project.org>
Sent: Wednesday, November 23, 2011 10:34 AM
Subject: [R] Is there an easier way to iterate over multiple data frames in R?
> for (d in paste('df', 1:3, sep='')) {
+ assign(d, as.data.frame(replicate(3, rnorm(4))))
+ }
> dats = list(df1,df2,df3)
> for (i in 1:length(dats)) {
+ names(dats[[i]]) = c('w', 'l', 'h')
+ }
> dats
[[1]]
w l h
1 1.24319239 -0.05543649 0.05409178
2 0.05124331 -1.89346950 0.33896273
3 -1.69686777 -0.35963008 -0.91720034
4 1.30786112 -0.23953238 0.94139356
[[2]]
w l h
1 -1.238519 -0.12352187 -1.2577607
2 1.180469 2.38836107 2.9139199
3 1.494369 -0.07088712 0.2372746
4 1.942535 1.47911615 1.1431675
[[3]]
w l h
1 1.0198692 -1.4222194 1.9486072
2 0.3057461 1.7630326 -0.6501801
3 -0.5576854 -1.1637263 -0.1782680
4 0.6625268 0.6913202 0.9588915
> i = 1
> for (n in paste('df', 1:3, sep='')) {
+ assign(n, dats[[i]])
+ i = i+1
+ }
> df1
w l h
1 1.24319239 -0.05543649 0.05409178
2 0.05124331 -1.89346950 0.33896273
3 -1.69686777 -0.35963008 -0.91720034
4 1.30786112 -0.23953238 0.94139356
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______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
