How to subset a data.table object in R by ignoring a value in one of the columns?


To subset a data.table object in R by ignoring a value in one of the columns, we can follow the below steps −

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

  • Then, use single square brackets to subset the data.table object by ignoring a value in one of the columns.

Example

Create the data.table object

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

library(data.table)
x<-sample(1:3,25,replace=TRUE)
y<-sample(1:4,25,replace=TRUE)
z<-sample(1:3,25,replace=TRUE)
DT<-data.table(x,y,z)
DT

Output

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

    x y z
1:  1 1 1
2:  1 3 1
3:  1 4 3
4:  3 3 1
5:  1 4 1
6:  1 2 3
7:  1 3 2
8:  1 3 1
9:  2 4 3
10: 1 4 3
11: 3 3 1
12: 3 2 2
13: 3 1 2
14: 2 4 2
15: 3 3 1
16: 3 2 1
17: 1 1 3
18: 2 4 1
19: 3 4 2
20: 3 2 1
21: 2 2 1
22: 3 4 1
23: 3 3 1
24: 1 1 1
25: 2 4 1
x y z

Subset the data.table object by ignoring a value in one of the columns

Using single square brackets to subset the data.table object DT by ignoring 4 in column y as shown below −

library(data.table)
x<-sample(1:3,25,replace=TRUE)
y<-sample(1:4,25,replace=TRUE)
z<-sample(1:3,25,replace=TRUE)
DT<-data.table(x,y,z)
DT[DT$y!=4,]

Output

    x y z
1:  1 1 1
2:  1 3 1
3:  3 3 1
4:  1 2 3
5:  1 3 2
6:  1 3 1
7:  3 3 1
8:  3 2 2
9:  3 1 2
10: 3 3 1
11: 3 2 1
12: 1 1 3
13: 3 2 1
14: 2 2 1
15: 3 3 1
16: 1 1 1

Updated on: 10-Nov-2021

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