Lets take mtcars as example and create a new variable:
mtcars$name <- rownames(mtcars)
mtcars[,] <- lapply(mtcars, factor)
mtcars[,] <- lapply(mtcars, as.numeric)
Now the names are converted into numerics which i definitely dont want
> mtcars
mpg cyl disp hp drat wt qsec vs am gear carb name
Mazda RX4 16 2 13 11 16 9 6 1 2 2 4 18
Mazda RX4 Wag 16 2 13 11 16 12 10 1 2 2 4 19
Datsun 710 19 1 6 6 15 7 22 2 2 2 1 5
Hornet 4 Drive 17 2 16 11 5 16 24 2 1 1 1 13
Hornet Sportabout 13 3 23 15 6 18 10 1 1 1 2 14
Valiant 12 2 15 9 1 19 29 2 1 1 1 31
Duster 360 3 3 23 20 7 21 5 1 1 1 4 7
Merc 240D 20 1 12 2 11 15 27 2 1 2 2 21
It is possible that type.convert would suit your needs. It coerces its input to the most basic data type that can represent it. Thus, it would turn a character column that contains numbers that can be represented as integer into an integer column.
mtcars$name <- rownames(mtcars)
str(mtcars)
# 'data.frame': 32 obs. of 12 variables:
# $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
# $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
# $ disp: num 160 160 108 258 360 ...
# $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
# $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
# $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
# $ qsec: num 16.5 17 18.6 19.4 17 ...
# $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
# $ am : num 1 1 1 0 0 0 0 0 0 0 ...
# $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
# $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
# $ name: chr "Mazda RX4" "Mazda RX4 Wag" "Datsun 710" "Hornet 4 Drive" ...
mtcars[,] <- lapply(mtcars, factor)
str(mtcars)
# 'data.frame': 32 obs. of 12 variables:
# $ mpg : Factor w/ 25 levels "10.4","13.3",..: 16 16 19 17 13 12 3 20 19 14 ...
# $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
# $ disp: Factor w/ 27 levels "71.1","75.7",..: 13 13 6 16 23 15 23 12 10 14 ...
# $ hp : Factor w/ 22 levels "52","62","65",..: 11 11 6 11 15 9 20 2 7 13 ...
# $ drat: Factor w/ 22 levels "2.76","2.93",..: 16 16 15 5 6 1 7 11 17 17 ...
# $ wt : Factor w/ 29 levels "1.513","1.615",..: 9 12 7 16 18 19 21 15 13 18 ...
# $ qsec: Factor w/ 30 levels "14.5","14.6",..: 6 10 22 24 10 29 5 27 30 19 ...
# $ vs : Factor w/ 2 levels "0","1": 1 1 2 2 1 2 1 2 2 2 ...
# $ am : Factor w/ 2 levels "0","1": 2 2 2 1 1 1 1 1 1 1 ...
# $ gear: Factor w/ 3 levels "3","4","5": 2 2 2 1 1 1 1 2 2 2 ...
# $ carb: Factor w/ 6 levels "1","2","3","4",..: 4 4 1 1 2 1 4 2 2 4 ...
# $ name: Factor w/ 32 levels "AMC Javelin",..: 18 19 5 13 14 31 7 21 20 22 ...
mtcars[,] <- lapply(mtcars, function(x) type.convert(as.character(x), as.is = TRUE))
str(mtcars)
#'data.frame': 32 obs. of 12 variables:
#$ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
#$ cyl : int 6 6 4 6 8 6 8 4 4 6 ...
#$ disp: num 160 160 108 258 360 ...
#$ hp : int 110 110 93 110 175 105 245 62 95 123 ...
#$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
#$ wt : num 2.62 2.88 2.32 3.21 3.44 ...
#$ qsec: num 16.5 17 18.6 19.4 17 ...
#$ vs : int 0 0 1 1 0 1 0 1 1 1 ...
#$ am : int 1 1 1 0 0 0 0 0 0 0 ...
#$ gear: int 4 4 4 3 3 3 3 4 4 4 ...
#$ carb: int 4 4 1 1 2 1 4 2 2 4 ...
#$ name: chr "Mazda RX4" "Mazda RX4 Wag" "Datsun 710" "Hornet 4 Drive" ...
If you don't store the original column classes before you turn the columns into factors, there is no way to restore this information completely. However, that shouldn't be necessary anyway.