# How to multiply corresponding row values in a data.table object with single row data.table object in R?

R ProgrammingServer Side ProgrammingProgramming

#### Artificial Intelligence : The Future Of Programming

15 Lectures 54 mins

#### Beyond Basic Programming - Intermediate Python

Most Popular

36 Lectures 3 hours

#### C Programming from scratch- Master C Programming

Best Seller

60 Lectures 8 hours

To multiply row values in a data.table object having multiple rows with single row data.table object in R, we can follow the below steps −

• First of all, create a data.table object with multiple rows and a data.table object with single row.

• Then, use mapply function to multiply row values in those objects.

## Example

#### Create the first data.table object

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

library(data.table)
x1<-sample(1:10,25,replace=TRUE)
x2<-sample(1:10,25,replace=TRUE)
DT1<-data.table(x1,x2)
DT1

## Output

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

     x1 x2
1:   8  1
2:   4  2
3:   8  5
4:   4  1
5:  10  2
6:   5 10
7:   9  3
8:   6  5
9:   1  6
10:  7  1
11:  9  7
12:  8  9
13:  4 10
14: 10  6
15:  1  4
16:  8  1
17: 10  4
18:  7  1
19:  3  1
20:  3  7
21:  2  8
22:  4  9
23:  5  8
24:  4  7
25:  3  1
x1 x2

Create the second data.table object

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

DT2<-data.table(y1=5,y2=0)
DT2

## Output

   y1 y2
1: 5  0

Multiply values from two data.table objects

Using mapply function to multiply row values in the data.table object DT1 having multiple rows with single row data.table object DT2 −

library(data.table)
x1<-sample(1:10,25,replace=TRUE)
x2<-sample(1:10,25,replace=TRUE)
DT1<-data.table(x1,x2)
DT2<-data.table(y1=5,y2=0)
mapply(*,DT1,DT2)

## Output

       x1 x2
[1,]   40 0
[2,]   20 0
[3,]   40 0
[4,]   20 0
[5,]   50 0
[6,]   25 0
[7,]   45 0
[8,]   30 0
[9,]    5 0
[10,]  35 0
[11,]  45 0
[12,]  40 0
[13,]  20 0
[14,]  50 0
[15,]   5 0
[16,]  40 0
[17,]  50 0
[18,]  35 0
[19,]  15 0
[20,]  15 0
[21,]  10 0
[22,]  20 0
[23,]  25 0
[24,]  20 0
[25,]  15 0