All,
Given a data frame and a list containing factor definitions for certain
columns, how can I apply those definitions from the list, rather than doing it
the standard way, as noted below. I'm lost in the world of do.call, assign,
paste, and can't find my way through. For example:
#set up df
y <- data.frame(colOne = c(1,2,3), colTwo = c("apple","pear","orange"))
factor.defs <- list(colOne = list(name = "colOne",
lvl = c(1,2,3,4,5,6)),
colTwo = list(name = "colTwo",
lvl = c("apple","pear","orange","fig","banana")))
#A standard way to define levels
y$colTwo <- factor(y$colTwo , levels =
c("apple","pear","orange","fig","banana"))
# I'd like to use the definitions locally but also pass them (but not the data)
to a function,
# so, rather than defining each manually each time, I'd like to loop through
the columns,
# call them by name, find the definitions in the list and use them from there.
Before I try to loop
# or use some form of apply, I'd like to get a single factor definition working.
# this doesn't seem to see the dataframe properly
do.call(factor,list((paste("y$",factor.defs[2][[1]]$name,sep="")),levels=factor.defs[2][[1]]$lvl))
#adding "as.name" doesn't help
do.call(factor,list(as.name(paste("y$",factor.defs[2][[1]]$name,sep="")),levels=factor.defs[2][[1]]$lvl))
#Here's my attempt to mimic the standard way, using assign. Ha! what a joke.
assign(as.name(paste("y$",factor.defs[2][[1]]$name,sep="")),
do.call(factor, list(as.name(paste("y$",factor.defs[2][[1]]$name,sep="")),
levels = factor.defs[2][[1]]$lvl)))
##Error in function (x = character(), levels, labels = levels, exclude = NA, :
## object 'y$colTwo' not found
Any help or perspective (or better way from the beginning!) would be greatly
appreciated.
Thanks in advance!
Tim
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