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How can I take multiple vectors and copy their data types to R?

I am looking for an elegant way to change the data types of several vectors in R.

I work with a training dataset: 426 students' answers to eight multiple-choice questions ( 1= correct, 0= incorrect), plus a column indicating which instructor ( 1, 2, or 3) taught his course.

In its current form, my data sits pretty in data.df, for example:

    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 values ques0xare not integers really . Rather, I believe that it is better to use R as experimental factors. The same applies to inst values.

I would like to turn all those intand numinfactors

, dataframe &mdash, factorData.df — :

    str(factorData.df)
    'data.frame': 426 obs. of  9 variables:
    $ ques01: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 1 1 1 2 ...
    $ ques02: Factor w/ 2 levels "0","1": 1 1 2 2 2 2 2 2 2 2 ...
    $ ques03: Factor w/ 2 levels "0","1": 1 1 2 2 1 1 2 2 1 2 ...
    $ ques04: Factor w/ 2 levels "0","1": 2 1 2 2 2 2 2 2 2 2 ...
    $ ques05: Factor w/ 2 levels "0","1": 1 1 1 1 2 1 1 1 1 1 ...
    $ ques06: Factor w/ 2 levels "0","1": 2 1 2 2 1 2 2 2 2 2 ...
    $ ques07: Factor w/ 2 levels "0","1": 1 1 2 2 1 2 2 1 1 2 ...
    $ ques08: Factor w/ 2 levels "0","1": 1 1 2 2 2 1 2 2 1 2 ...
    $ inst  : Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 1 ...

, , , , , (int -> factor num -> int, ).

, , , ,

- 9 factor(), ,

    factorData.df$ques01

R, stackoverflow. , , !

+5
2

R-Help.

, , :

# 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

lapply:

> data.df <- data.frame(lapply(data.df, factor))

for:

> for(i in 1:ncol(data.df)) data.df[,i] <- as.factor(data.df[,i])

, :

> 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 ...
+11

plyr:

# load the package and data
> library(plyr)
> data.df <- cars

colwise:

> data.df <- colwise(factor)(data.df)
> 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 ...

, colwise, lapply:

df <- as.data.frame(lapply(filtered, .fun, ...))
+5

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