How can I take multiple vectors and recode their datatypes in R?

Question

I'm looking for an elegant way to change multiple vectors' datatypes in R. I'm working with an educational dataset: 426 students' answers to eight multiple choice questions (`1` = correct, `0` = incorrect), plus a column indicating which instructor (`1, 2, or 3`) taught their course. As it stands, my data is sitting pretty in `data.df`, like this: ``` str(data.df) 'data.frame': 426 obs. of 9 variables: $ ques01: int 1 1 1 1 1 1 0 0 0 1 ... $ ques02: int 0 0 1 1 1 1 1 1 1 1 ... $ ques03: int 0 0 1 1 0 0 1 1 0 1 ... $ ques04: int 1 0 1 1 1 1 1 1 1 1 ... $ ques05: int 0 0 0 0 1 0 0 0 0 0 ... $ ques06: int 1 0 1 1 0 1 1 1 1 1 ... $ ques07: int 0 0 1 1 0 1 1 0 0 1 ... $ ques08: int 0 0 1 1 1 0 1 1 0 1 ... $ inst : num 1 1 1 1 1 1 1 1 1 1 ... ``` But those `ques0x` values aren't really integers. Rather, I think it's better to have R treat them as experimental factors. Same goes for the "inst" values. I'd love to turn all those `int`s and `num`s into `factors` Ideally, an elegant solution sh…

Accepted Answer

This was also answered in R-Help. I imagine that there's a better way to do it, but here are two options: ``` # use a sample data set > str(cars) 'data.frame': 50 obs. of 2 variables: $ speed: num 4 4 7 7 8 9 10 10 10 11 ... $ dist : num 2 10 4 22 16 10 18 26 34 17 ... > data.df <- cars ``` You can use `lapply`: ``` > data.df <- data.frame(lapply(data.df, factor)) ``` Or a `for` statement: ``` > for(i in 1:ncol(data.df)) data.df[,i] <- as.factor(data.df[,i]) ``` In either case, you end up with what you want: ``` > str(data.df) 'data.frame': 50 obs. of 2 variables: $ speed: Factor w/ 19 levels "4","7","8","9",..: 1 1 2 2 3 4 5 5 5 6 ... $ dist : Factor w/ 35 levels "2","4","10","14",..: 1 3 2 9 5 3 7 11 14 6 ... ```

How can I take multiple vectors and recode their datatypes in R?

Solution

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