coding variable values into classes using R

Question

I have a set of data in which I need to code values of certain variables (numeric) into 3 classes.

My data set is similar to this but has 60 more variables:

anim <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
wt <- c(181,179,180.5,201,201.5,245,246.4,189.3,301,354,369,205,199,394,231.3)
data <- data.frame(anim,wt)

> data
   anim    wt
1     1 181.0
2     2 179.0
3     3 180.5
4     4 201.0
5     5 201.5
6     6 245.0
7     7 246.4
8     8 189.3
9     9 301.0
10   10 354.0
11   11 369.0
12   12 205.0
13   13 199.0
14   14 394.0
15   15 231.3

I need to code values of the variable "wt" up into 3 classes: (wt >= 179 & wt < 200) = 1; (wt >= 200 & wt < 300) = 2; (wt > 300) = 3

which should give me this

> data2
   anim    wt SWT
1     1 181.0   1
2     2 179.0   1
3     3 180.5   1
4     4 201.0   2
5     5 201.5   2
6     6 245.0   2
7     7 246.4   2
8     8 189.3   1
9     9 301.0   3
10   10 354.0   3
11   11 369.0   3
12   12 205.0   2
13   13 199.0   1
14   14 394.0   3
15   15 231.3   2

Answer 1

The cut method as outlined by @Greg is probably what you want here. One thing to note is that cut returns a factor by default, which you can suppress by supplying labels = FALSE to return the integer values:

cut(data$wt, c(178, 200, 300, Inf), labels = FALSE)

Alternatively, if your cutting does not lend itself to natural breaks, you can use ifelse(). You can "nest" the ifelse statements similar to Excel. I use "with" to cut down on the typing needed:

data$group2 <- with(data, ifelse(wt >= 179 & wt < 200, 1, 
  ifelse(wt >= 200 & wt < 300, 2, 3))
)

Answer 2

You can try cut

anim <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15) 
wt <-c(181,179,180.5,201,201.5,245,246.4,
189.3,301,354,369,205,199,394,231.3) 
data <- data.frame(anim,wt)

EDIT: fixed group - right = FALSE, got rid of split example.

group = cut(data$wt, c(178, 200, 300, Inf), right=FALSE)


data$swt = as.numeric(group)
data
   anim    wt swt
1     1 181.0   1
2     2 179.0   1
3     3 180.5   1
4     4 201.0   2
5     5 201.5   2
6     6 245.0   2
7     7 246.4   2
8     8 189.3   1
9     9 301.0   3
10   10 354.0   3
11   11 369.0   3
12   12 205.0   2
13   13 199.0   1
14   14 394.0   3
15   15 231.3   2
>