Multiply Vector Values with Data Frame Columns in R

To multiply vector values in sequence with data frame columns in R, we can follow the below steps −

• First of all, create a data frame.

• Then, create a vector.

• After that, use t function for transpose and multiplication sign * to multiply vector values in sequence with data frame columns.

Example 1

Create the data frame

Let’s create a data frame as shown below −

x1<-rpois(25,2)
x2<-rpois(25,2)
x3<-rpois(25,2)
df1<-data.frame(x1,x2,x3)
df1

Output

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

   x1 x2 x3
1  3  2  1
2  1  0  3
3  1  1  2
4  2  1  1
5  5  1  0
6  4  2  3
7  1  2  3
8  1  2  2
9  2  1  0
10 0  1  2
11 0  2  3
12 1  1  2
13 4  3  0
14 0  3  0
15 4  5  2
16 4  2  2
17 5  4  5
18 1  3  1
19 1  3  4
20 1  0  5
21 3  4  1
22 4  0  0
23 1  2  2
24 2  2  1
25 1  0  1

Create the vector

Let’s create a vector as shown below −

v1<-c(1,5,10)
v1

Output

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

[1] 1 5 10

Multiply vector values in sequence with data frame columns

Using t function for transpose and multiplication sign * to multiply v1 values in sequence with columns of data frame df1 as shown below −

x1<-rpois(25,2)
x2<-rpois(25,2)
x3<-rpois(25,2)
df1<-data.frame(x1,x2,x3)
v1<-c(1,5,10)
t(t(df1)*v1)

Output

     x1 x2 x3
[1,]  1 20 10
[2,]  2 10 10
[3,]  2  5 40
[4,]  4 30 20
[5,]  1 30 30
[6,]  3  0 10
[7,]  2  0 10
[8,]  1 20 40
[9,]  1 15 50
[10,] 1  0 10
[11,] 3 25 30
[12,] 0 15  0
[13,] 1 25 40
[14,] 3  5 30
[15,] 3 10  0
[16,] 2 10 10
[17,] 2 10 20
[18,] 0 15 10
[19,] 1 15 30
[20,] 3  5 50
[21,] 1 10 10
[22,] 0 20 40
[23,] 1 25 10
[24,] 1  5  0
[25,] 3 10  0

Example 2

Create the data frame

Let’s create a data frame as shown below −

y1<-round(rnorm(25),2)
y2<-round(rnorm(25),2)
y3<-round(rnorm(25),2)
df2<-data.frame(y1,y2,y3)
df2

Output

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

    y1     y2    y3
1  -0.20 -0.19  1.14
2  -0.04 -0.99  2.09
3   0.47  0.83  0.49
4  -0.23 -0.24  0.18
5   0.02 -1.03 -2.62
6   1.52 -0.99 -1.16
7  -0.17 -0.38  1.87
8   0.64 -0.16  0.62
9   1.32  0.02 -1.07
10 -0.37  2.05  0.52
11  0.25 -0.29  1.19
12  0.69 -0.58  0.93
13  1.50 -0.34  1.32
14  1.06 -1.27  1.04
15  0.16  0.87  0.84
16 -0.81  0.31  0.11
17  1.50 -0.53  1.95
18 -1.27  2.88 -0.88
19  0.37 -0.14  2.47
20  1.36 -1.51  1.36
21  1.29 -0.40 -0.24
22 -1.12  0.99  1.44
23 -0.17 -1.07 -0.22
24 -0.95  1.71 -0.46
25  0.00 -0.63  1.02

Create the vector

Let’s create a vector as shown below −

v2<-c(10,20,10)
v2

Output

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

[1] 10 20 10

Multiply vector values in sequence with data frame columns

Using t function for transpose and multiplication sign * to multiply v2 values in sequence with columns of data frame df2 as shown below −

y1<-round(rnorm(25),2)
y2<-round(rnorm(25),2)
y3<-round(rnorm(25),2)
df2<-data.frame(y1,y2,y3)
v2<-c(10,20,10)
t(t(df2)*v2)

Output

       y1    y2     y3
[1,]  -2.0  -3.8   11.4
[2,]  -0.4  -19.8  20.9
[3,]   4.7   16.6  4.9
[4,]  -2.3  -4.8   1.8
[5,]   0.2  -20.6 -26.2
[6,]   15.2 -19.8 -11.6
[7,]  -1.7  -7.6   18.7
[8,]   6.4  -3.2   6.2
[9,]   13.2  0.4  -10.7
[10,] -3.7   41.0  5.2
[11,]  2.5  -5.8   11.9
[12,]  6.9  -11.6  9.3
[13,]  15.0 -6.8   13.2
[14,]  10.6 -25.4  10.4
[15,]  1.6   17.4  8.4
[16,] -8.1   6.2    1.1
[17,]  15.0 -10.6  19.5
[18,] -12.7  57.6  -8.8
[19,]  3.7  -2.8   24.7
[20,]  13.6 -30.2  13.6
[21,]  12.9 -8.0  -2.4
[22,] -11.2  19.8  14.4
[23,] -1.7  -21.4 -2.2
[24,] -9.5   34.2 -4.6
[25,]  0.0  -12.6 10.2