On Nov 17, 2010, at 6:57 PM, Sam Albers wrote:
On Wed, Nov 17, 2010 at 3:49 PM, David Winsemius <dwinsem...@comcast.net
> wrote:
On Nov 17, 2010, at 6:27 PM, Sam Albers wrote:
Hello all,
I have a fairly simple data manipulation question. Say I have a
dataframe
like this:
dat <- as.data.frame(runif(7, 3, 5))
dat$cat <- factor(c("1","4","13","1","4","13","13A"))
dat
runif(7, 3, 5) cat
1 3.880020 1
2 4.062800 4
3 4.828950 13
4 4.761850 1
5 4.716962 4
6 3.868348 13
7 3.420944 13A
Under the dat$cat variable the 13A value is an analytical
replicate. For my
purposes I would like to drop all values that are not an integer
(i.e. 13A)
from the dataframe. Can anyone recommend a way to drop all rows
where the
cat value is a non-integer?
DW----
dat[!is.na(as.numeric(as.character(dat$cat))), ]
(You do get a warning about coercion to NA's but that is a good
sign since that is what we were trying to exclude in the first
place.)
SA---
Apologies. This worked fine but I didn't quite outline that I also
wanted to drop the unused levels of the factor as well. drop=TRUE
doesn't seem to work, so can anyone suggest a way to drop the factor
levels in addition to the values?
> sd <- dat[!is.na(as.numeric(as.character(dat$cat))), ]
Warning message:
In `[.data.frame`(dat, !is.na(as.numeric(as.character(dat$cat))), :
NAs introduced by coercion
> str(sd)
'data.frame': 6 obs. of 2 variables:
$ runif(7, 3, 5): num 3.88 4.06 4.83 4.76 4.72 ...
$ cat : Factor w/ 4 levels "1","13","13A",..: 1 4 2 1 4 2
Right. Well, pretty simple actually:
dat2 <- dat[!is.na(as.numeric(as.character(dat$cat))), ]
dat2$cat <- factor(dat2$cat) # removes the no-longer-existent levels
<restored original quote levels and stripped a bunch of "signage">
--
David Winsemius, MD
West Hartford, CT
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