On 10/6/2005 9:14 AM, Florence Combes wrote: > Dear all, > > I try for long to understand exactly what is the factor type and especially > how it works, but it seems too difficult for me.... > I read paragraphs about it, and I understand quite well what it is (I think) > but I still can't figure how to deal with. > Especially these 2 mysteries (for me) : > > 1st when I make a dataframe (with the as.data.frame() or the data.frame() > commands) from vectors, it seems that some "columns" of the dataframe (which > where vectors) are factors and some not, but I didn't find an explanation > for which become factor and which don't. > (I know I can use I() to avoid the factor transformaton but I think it is > not an optimal solution to avoid the factor type just because I don't kno > how to deal with)
This is described in the ?data.frame man page: "Character variables passed to 'data.frame' are converted to factor columns unless protected by 'I'." > 2d I can't manage to deal with factors, so when I have some, I transform > them in vectors (with levels()), but I think I miss the power and utility of > the factor type ? levels() is not the conversion you want. That lists all the levels, but it doesn't tell you how they correspond to individual observations. For example, > df <- data.frame(x=1:3, y=c('a','b','a')) > df x y 1 1 a 2 2 b 3 3 a > levels(df$y) [1] "a" "b" If you need to convert back to character values, use as.character(): > as.character(df$y) [1] "a" "b" "a" For many purposes, you can ignore the fact that your data is stored as a factor instead of a character vector. There are a few differences: 1. You can't compare the levels of a factor unless you declared it to be ordered: > df$y[1] > df$y[2] [1] NA Warning message: > not meaningful for factors in: Ops.factor(df$y[1], df$y[2]) but > df$y <- ordered(df$y) > df$y[1] > df$y[2] [1] FALSE However, you need to watch out here: the comparison is done by the order of the factors, not an alphabetic comparison of their names: > levels(df$y) <- c("before", "after") > df x y 1 1 before 2 2 after 3 3 before > df$y[1] > df$y[2] [1] FALSE 2. as.integer() works differently on factors: it gets the position in the levels vector. For example, > as.integer(df$y) [1] 1 2 1 > as.integer(as.character(df$y)) [1] NA NA NA Warning message: NAs introduced by coercion There are other differences, but these are the two main ones that are likely to cause you trouble. Duncan Murdoch ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html