On Jan 1, 2010, at 10:34 PM, Girish A.R. wrote:
Hi folks,
Wish y'all a Happy New Year 2010!
I need some help with the following:
Say I have lots of data sets, on which I have to apply a certain
function on
the same set of columns in each of the data set. Let's take, for ex,
the
typical data set is:
df1 <- as.data.frame(cbind(rnorm(10),rnorm(10)))
names(df1)[1] <- "A"
names(df1)[2] <- "B"
There are many such data sets, df2,df3,... I have the names stored
in a list
DF <- cbind("df1","df2",...,"df100")
Unfortunately, that is not a list, but rather a character vector
> DF <- cbind("df1","df2","df100")
> str(DF)
chr [1, 1:3] "df1" "df2" "df100"
Instead define it as a list of objects (i.e., with no quotes):
LL <- list(df1, df2, .... , df100)
#and then
lapply(LL, function(x) lsfit(x$A,x$B) )
--
Daid.
I now need to apply the following function:
a <- lsfit(df1$A,df1$B)
and stack up the following results:
a$coef
Intercept X
-0.1479750 0.2485416
So, I would end up with as many rows as there are data sets.
I think sapply would be the function I should be looking for (at
least I
have used it in the case of applying a function across different
columns of
the same data set), but for some reason I'm not able to nail down
the final
stages in this case.
Earlier, I used something like the following in the case of applying a
function across all columns(except the first) of the same data set:
my.func <- function(x){
mod <- lrm(my.data$y ~ x)
data.frame(t(anova(mod)[1, ]), R2 = mod$stats[10])
sapply(my.data[,-1],my.func)
Where I need help is how to pass the reference of the names of the
different
data sets to the sapply funtion.
Thanks!
-Girish
====================================
sessionInfo()
R version 2.10.0 (2009-10-26)
i386-pc-mingw32
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] grid stats graphics grDevices utils datasets
methods
base
other attached packages:
[1] lattice_0.17-26 RWinEdt_1.8-2 ggplot2_0.8.5 digest_0.4.2
reshape_0.8.3
[6] plyr_0.1.9 proto_0.3-8
loaded via a namespace (and not attached):
[1] Formula_0.2-0 kinship_1.1.0-23 MASS_7.3-4 nlme_3.1-96
plm_1.2-1
[6] sandwich_2.2-4 splines_2.10.0 survival_2.35-8 tools_2.10.0
--
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and provide commented, minimal, self-contained, reproducible code.
