Others have shown how to do this, but a better approach may be to load your
.Rdata file into a new environment rather than the global environment, then you
can work with the environment (and all the objects in it) using lapply, or
loops with [[]] instead of fighting with get and assign.
Something like:
> mydfs <- new.env()
> load( '.Rdata', env=mydfs
> mydfs <- lapply( mydfs, function(x) { x$ResultValue <-
> as.numeric(x$ResultValue); x} )
Or
> mydfs <- lapply( mydfs, function(x) within(x, ResultValue <-
> as.numeric(ResultValue) ) )
Or
> for( frame in ls(env=mydfs) ) {
+ mydfs[[frame]]$ResultValue <- as.numeric( mydfs[[frame]]$ResultValue )
+ }
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Sarah Henderson
Sent: Thursday, July 28, 2011 5:09 PM
To: R List
Subject: [R] Looping through data sets to change column from character to
numeric
Greetings to all --
I am having a silly problem that I just can't solve. Someone has given me
an .RData file will hundreds of data frames. Each data frame has a column
named ResultValue, currently character when it should be numeric. I want to
loop through all of the data frames to change the variable to numeric, but I
cannot figure out how to do it. My best guess was along the lines of:
frames = ls()
for (frame in frames){
assign(frame, get(frame), .GlobalEnv)
frame[,"ResultValue"] = as.numeric(frame[,"ResultValue"])
}
It doesn't work. After the assign() the frame object remains the character
name of the dataframe I am trying to change. If I do the following, the
TEST object comes out just fine.
frames = ls()
for (frame in frames){
assign("TEST", get(frame), .GlobalEnv)
TEST[,"ResultValue"] = as.numeric(TEST[,"ResultValue"])
}
Seems like it should be simple, but I am misunderstanding something and not
following the logic. Any insight?
Thanks,
Sarah
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and provide commented, minimal, self-contained, reproducible code.
