Scale Columns in Data Table Object in R

To scale some columns in data.table object in R, we can follow the below steps −

• First of all, create a data.table object.

• hen, subset the columns with single square brackets and use lapply, list and scale function to scale those columns.

Example

Create the data.table object

Let’s create a data.table object as shown below −

library(data.table)
var1<-rpois(25,5)
var2<-rpois(25,2)
var3<-rpois(25,5)
var4<-rpois(25,3)
DT<-data.table(var1,var2,var3,var4)
DT

Output

On executing, the above script generates the below output(this output will vary on your system due to randomization) −

  var1 var2 var3 var4
1:   5    2  1   2
2:   3    5  4   2
3:   6    2  7   3
4:  10    3  5   3
5:   3    5  3   0
6:   4    1  6   2
7:   4    1  5   3
8:   3    1  6   0
9:   2    2  9   1
10:  2    1  6   6
11:  5    2  5   2
12:  3    1  2   3
13:  4    4  4   1
14:  8    0  5   2
15:  6    1  2   2
16:  4    3  3   3
17:  2    1  7   2
18:  8    2  7   3
19:  9    3  7   0
20:  6    2  6   4
21:  8    2  4   4
22:  4    0  3   2
23: 10    2  4   4
24:  5    3  6   7
25:  5    1  6   1
   var1 var2 var3 var4

Scale some columns

Subset the var1 and var2 columns with single square brackets and use lapply, list and scale function to scale those columns as shown below −

DT[,c("var1","var2"):=lapply(list(var1,var2),scale)]
DT

Output

      var1         var2   var3 var4
1:  -0.06546537  0.0000000 1   2
2:  -0.88378246  2.2677868 4   2
3:   0.34369318  0.0000000 7   3
4:   1.98032735  0.7559289 5   3
5:  -0.88378246  2.2677868 3   0
6:  -0.47462391 -0.7559289 6   2
7:  -0.47462391 -0.7559289 5   3
8:  -0.88378246 -0.7559289 6   0
9:  -1.29294100  0.0000000 9   1
10: -1.29294100 -0.7559289 6   6
11: -0.06546537  0.0000000 5   2
12: -0.88378246 -0.7559289 2   3
13: -0.47462391  1.5118579 4   1
14:  1.16201027 -1.5118579 5   2
15:  0.34369318 -0.7559289 2   2
16: -0.47462391  0.7559289 3   3
17: -1.29294100 -0.7559289 7   2
18:  1.16201027  0.0000000 7   3
19:  1.57116881  0.7559289 7   0
20:  0.34369318  0.0000000 6   4
21:  1.16201027  0.0000000 4   4
22: -0.47462391 -1.5118579 3   2
23:  1.98032735  0.0000000 4   4
24: -0.06546537  0.7559289 6   7
25: -0.06546537 -0.7559289 6   1
        var1        var2  var3 var4