How to replace a complete column in an R data frame?

To replace a complete column in an R data frame, we can set the original one to new values by using delta operator. For example, if we have a data frame called df that contains a column x which 500 has values from normal distribution then to replace it with the normal distribution having a mean of 25 can be done as df$x<−rnorm(500,5).

Example1

 Live Demo

Consider the below data frame −

x1<−rpois(20,2)
x2<−rpois(20,2)
x3<−rpois(20,3)
df1<−data.frame(x1,x2,x3)
df1

Output

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

Replacing x3 with Poisson distribution having lambda 2 −

Example

df1$x3<−rpois(20,2)
df1

Output

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

Example2

 Live Demo

y1<−rnorm(20,1,0.05)
y2<−rnorm(20,1,0.75)
y3<−rnorm(20,1,0.05)
y4<−rnorm(20,1,0.05)
df2<−data.frame(y1,y2,y3,y4)
df2

Output

y1 y2 y3 y4
1 1.0141018 0.71738148 0.9420311 1.0009205
2 1.0258060 1.03202326 1.0183309 1.0953612
3 0.9743657 1.58046651 1.0517233 1.0596325
4 1.0199483 1.08089945 0.9873335 0.9910522
5 1.0740019 2.13191506 1.0805077 1.0352464
6 1.0504327 1.55207108 1.0105741 0.9503119
7 0.9656107 1.51496959 1.0856465 1.0721738
8 1.0314142 −0.62997358 0.9007254 0.9555474
9 0.9688579 2.05252761 0.9920891 0.9693772
10 0.9811555 1.58630688 0.9550110 0.9611265
11 0.9594506 1.49768858 0.9792084 0.9442541
12 0.9891804 0.50237995 0.8821927 1.0816134
13 1.0939416 0.16319086 1.0682660 0.9552987
14 1.0437989 2.06159460 1.0034599 0.9708994
15 0.9660916 1.21363074 0.9780202 0.9961647
16 1.0634504 0.82467522 1.0184935 1.0586482
17 0.9907623 1.06935013 1.0507246 0.9516461
18 1.0336085 2.07268738 0.9972536 0.9815386
19 1.0366192 2.20583375 1.0393763 0.9332535
20 1.0861114 0.02966648 1.0502028 0.9452250

Replacing y2 with Normal distribution having mean 1 and standard deviation 0.05 −

Example

df2$y2<−rnorm(20,1,0.05)
df2

Output

y1 y2 y3 y4
1 1.0141018 0.9238429 0.9420311 1.0009205
2 1.0258060 0.9940841 1.0183309 1.0953612
3 0.9743657 0.9705115 1.0517233 1.0596325
4 1.0199483 0.9521452 0.9873335 0.9910522
5 1.0740019 0.9531263 1.0805077 1.0352464
6 1.0504327 1.0587658 1.0105741 0.9503119
7 0.9656107 0.9558315 1.0856465 1.0721738
8 1.0314142 1.0368435 0.9007254 0.9555474
9 0.9688579 0.9117594 0.9920891 0.9693772
10 0.9811555 1.0072615 0.9550110 0.9611265
11 0.9594506 0.9935137 0.9792084 0.9442541
12 0.9891804 1.0018355 0.8821927 1.0816134
13 1.0939416 0.9531882 1.0682660 0.9552987
14 1.0437989 0.8805634 1.0034599 0.9708994
15 0.9660916 1.0378592 0.9780202 0.9961647
16 1.0634504 1.0431174 1.0184935 1.0586482
17 0.9907623 1.0666330 1.0507246 0.9516461
18 1.0336085 0.9449561 0.9972536 0.9815386
19 1.0366192 0.9172270 1.0393763 0.9332535
20 1.0861114 0.9739211 1.0502028 0.9452250