I have a data frame that is the result of a cast (reshape) operation. I
deleted the variable column and tried to melt the resulting data frame.
Depending on which method I use to delete the column I get different
error messages when melting:
> head(tinfos)
vpn group trial_no item relation trial_type rt variable #
1 102 2 1 4351 diag1 distractor 8471 fix_d 27
2 102 2 2 1214 id target 4072 fix_d 17
3 102 2 3 4213 diag1 distractor 7040 fix_d 27
4 102 2 4 1314 id target 4370 fix_d 15
5 102 2 5 2655 vert distractor 4397 fix_d 17
6 102 2 6 3322 horiz distractor 6132 fix_d 26
> tinfos$variable <- NULL
> melt(tinfos)
Error: id variables not found in data: variable
Or:
> tinfos2 <- tinfos[,-match("variable",names(tinfos))]
> melt(tinfos2)
Error in `rownames<-`(`*tmp*`, value = character(0)) :
attempt to set rownames on object with no dimensions
In addition: Warning messages:
1: In `[<-.factor`(`*tmp*`, ri, value = c(8471L, 4072L, 7040L, 4370L, :
invalid factor level, NAs generated
2: In `[<-.factor`(`*tmp*`, ri, value = c(0L, 0L, 1L, 0L, 0L, 0L, 0L, :
invalid factor level, NAs generated
I figure there must be some internal inconsistency in the data frame
after deletion. Does anybody have an idea how to fix that?
Thanks!
Titus
On Thu, Jan 22, 2009 at 8:01 AM, Titus von der Malsburg <malsburg at gmail.com> wrote:> I have a data frame that is the result of a cast (reshape) operation. I > deleted the variable column and tried to melt the resulting data frame. > Depending on which method I use to delete the column I get different > error messages when melting: > > > head(tinfos) > vpn group trial_no item relation trial_type rt variable # > 1 102 2 1 4351 diag1 distractor 8471 fix_d 27 > 2 102 2 2 1214 id target 4072 fix_d 17 > 3 102 2 3 4213 diag1 distractor 7040 fix_d 27 > 4 102 2 4 1314 id target 4370 fix_d 15 > 5 102 2 5 2655 vert distractor 4397 fix_d 17 > 6 102 2 6 3322 horiz distractor 6132 fix_d 26 > > tinfos$variable <- NULL > > melt(tinfos) > Error: id variables not found in data: variableCast stores some extra information in the data frame that makes future melting a bit easier, provided that you don't delete any of the columns. Since you have, you need to throw away the extra info with: tinfos <- as.data.frame(tinfos) Regards, Hadley -- http://had.co.nz/