Question

I’m having some trouble indexing data.frames in R. I’m an R beginner. I have a data.frame called d which has 35512 columns and 77 rows. I have a list called rd which contains 35512 elements. I’d like all the columns of d which correspond to the items in rd less than 100. Here’s what I’m doing:

# just to prove I'm not crazy
> length(colnames(d))
[1] 35512
> length(rownames(d))
[1] 77
> length(rd)
[1] 35512
# find all the elements of rd less than 100 (+ unnecessary faffing?)
> i <- unlist(rd<100)
> names(i) <- NULL
# try to extract all the elements of d corresponding to rd < 100
> d <- d[,i]
Error in `[.data.frame`(d, , i) : undefined columns selected

I don’t really want to be doing the unlist and names(i) <- NULL stuff but I’m getting seriously paranoid. Can anyone help with what the hell this error message means?

In case it helps, the rd variable is created using the following:

rd = lapply(lapply(d, range), diff)

Which hopefully tells me the difference in the range of each column of d.

P.S. bonus awesomeness for anyone who can tell me a command to find the shape of a data.frame other than querying the length of its row and column names.

Edit: Here’s what rd looks like:

> rd[1:3]
$`10338001`
[1] 7198.886

$`10338003`
[1] 4748.963

$`10338004`
[1] 3173.046

and when I’ve done my faffing, i looks like this:

> i[7:10]
[1] FALSE FALSE FALSE  TRUE

Answer 1

Have you tried this:

d[,rd < 100]

Here’s a self-contained example:

d <- data.frame(matrix(1:100, ncol=10))
rd <- as.list(1:10)
d[,rd < 5]

To get the shape of a dataframe, use nrow and ncol.

Edit:

Based on your response to my NA question, it sounds like you have non-logical values in your index that result from missing values in your list. The best thing to do is to first decide how you want to treat a missing value. Then deal with them using the is.na function (here I extend my example from above):

rd[[3]] <- NA
d[,rd < 5]
# => Error in `[.data.frame`(d, , rd < 5) : undefined columns selected

To deal with this, I will set that NA value to 0 (which means that it the respective column will be included in the final data.frame):

rd[is.na(rd)] <- 0
d[,rd < 5]

You need to decide for yourself what to do with the NA values.