Hi:
The simplest way to do it is to modify the input data frame by taking
out the records not having status live or dead and then redefining the
factor in the new data frame to get rid of the removed levels. Calling
your input data frame DF rather than data,
DF <- structure(list(FID = c(1L, 1L, 2L, 2L, 2L, 2L, 6L, 6L, 10L, 10L,
10L, 11L, 11L, 11L, 12L, 17L, 17L, 17L), IID = c(4621L, 4628L,
4631L, 4632L, 4633L, 4634L, 4675L, 4679L, 4716L, 4719L, 4721L,
4726L, 4728L, 4730L, 4732L, 4783L, 4783L, 4784L), STATUS = structure(c(2L,
1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 3L, 3L, 2L, 2L, 2L,
2L), .Label = c("dead", "live", "nosperm"), class = "factor")), .Names
= c("FID",
"IID", "STATUS"), class = "data.frame", row.names = c(NA, -18L
))
# The right hand side above came from dput(DF), where DF was created by
# DF <- read.table(textConnection("<your posted data>"), header = TRUE)
# Consider using dput() to represent your data in the future.
# Retain the records with status live or dead only
DF2 <- DF[DF$STATUS %in% c("live", "dead"), ]
# This does not get rid of the original levels...
levels(DF2$STATUS)
# ...so redefine the factor
DF2$STATUS <- factor(DF2$STATUS)
> str(DF2)
'data.frame': 16 obs. of 3 variables:
$ FID : int 1 1 2 2 2 2 6 6 10 10 ...
$ IID : int 4621 4628 4631 4632 4633 4634 4675 4679 4716 4719 ...
$ STATUS: Factor w/ 2 levels "dead","live": 2 1 2 2 2 2 2 1 1 2 ...
# now plot:
# (1) FID numeric
ggplot(DF2, aes(x = FID, fill = STATUS)) + geom_bar()
# (2) FID factor
ggplot(DF2, aes(x = factor(FID), fill = STATUS)) + geom_bar()
The second one makes more sense to me, but you may have reasons to
prefer the first.
Dennis
On Thu, Dec 13, 2012 at 4:38 AM, Yao He <[email protected]> wrote:
> FID IID STATUS
> 1 4621 live
> 1 4628 dead
> 2 4631 live
> 2 4632 live
> 2 4633 live
> 2 4634 live
> 6 4675 live
> 6 4679 dead
> 10 4716 dead
> 10 4719 live
> 10 4721 dead
> 11 4726 live
> 11 4728 nosperm
> 11 4730 nosperm
> 12 4732 live
> 17 4783 live
> 17 4783 live
> 17 4784 live
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