Grouping/recoding factors in the same data.frame

Question

Let's say I have a data frame like this:

df <- data.frame(a=letters[1:26],1:26)

And I would like to "re" factor a, b, and c as "a".

How do I do that?

Answer 1

One option is the recode() function in package car:

require(car)
df <- data.frame(a=letters[1:26],1:26)
df2 <- within(df, a <- recode(a, 'c("a","b","c")="a"'))
> head(df2)
  a X1.26
1 a     1
2 a     2
3 a     3
4 d     4
5 e     5
6 f     6

Example where a is not so simple and we recode several levels into one.

set.seed(123)
df3 <- data.frame(a = sample(letters[1:5], 100, replace = TRUE),
                  b = 1:100)
with(df3, head(a))
with(df3, table(a))

the last lines giving:

> with(df3, head(a))
[1] b d c e e a
Levels: a b c d e
> with(df3, table(a))
a
 a  b  c  d  e 
19 20 21 22 18

Now lets combine levels a and e into level Z using recode()

df4 <- within(df3, a <- recode(a, 'c("a","e")="Z"'))
with(df4, head(a))
with(df4, table(a))

which gives:

> with(df4, head(a))
[1] b d c Z Z Z
Levels: b c d Z
> with(df4, table(a))
a
 b  c  d  Z 
20 21 22 37

Doing this without spelling out the levels to merge:

## Select the levels you want (here 'a' and 'e')
lev.want <- with(df3, levels(a)[c(1,5)])
## now paste together
lev.want <- paste(lev.want, collapse = "','")
## then bolt on the extra bit
codes <- paste("c('", lev.want, "')='Z'", sep = "")
## then use within recode()
df5 <- within(df3, a <- recode(a, codes))
with(df5, table(a))

Which gives us the same as df4 above:

> with(df5, table(a))
a
 b  c  d  Z 
20 21 22 37 

Answer 2

You could do something like:

df$a[df$a %in% c("a","b","c")] <- "a"

---

UPDATE: More complicated factors.

Data <- data.frame(a=sample(c("Less than $50,000","$50,000-$99,999",
  "$100,000-$249,999", "$250,000-$500,000"),20,TRUE),n=1:20)
rows <- Data$a %in% c("$50,000-$99,999", "$100,000-$249,999")
Data$a[rows] <- "$250,000-$500,000"

Answer 3

there are two ways. if you don't want to drop the unused levels, ie "b" and "c", Joshua's solution is probably best.

if you want to drop the unused levels, then

df$a<-factor(ifelse(df$a%in%c("a","b","c"),"a",as.character(df$a)))

or

levels(df$a)<-ifelse(levels(df$a)%in%c("a","b","c"),"a",levels(df$a))