[R] Convert data frame containing time stamps to time series

[amvds at xs4all.nl]

I read records using scan:

dat<-data.frame(scan(file="KDA.csv",what=list(t="%m/%d/%y
%H:%M",f=0,p=0,d=0,o=0,s=0,a=0,l=0,c=0),skip=2,sep=",",nmax=np,flush=TRUE,na.strings=c("I/OTimeout","ArcOff-line")))

which results in:

> dat[1:5,]
             t     f    p  d  o   s    a  l c
1 1/21/09 5:01 16151  8.2 76 30 282 1060 53 7
2 1/21/09 5:02 16256  8.3 76 23 282 1059 54 7
3 1/21/09 5:03 16150  8.4 76 26 282 1059 55 7
4 1/21/09 5:04 16150  9.0 76 25 282 1051 57 6
5 1/21/09 5:05 15543 10.4 76  7 282 1024 58 6

I have been unable to find a way to convert this into a time series. I did
read the manuals and came across a way to coerce a data frame to a ts
object: as.ts()

Trouble is I do not know how to keep the timestamps in column t in the
data frame above. The t column is not strings. If I do:

plot.ts(dat)

I can see how the first graphics panel is indeed numbers not text. So I
think scan converted the text correctly per the format string I put in.

Much more difficult still. The datafiles I have contain invalid data,
missing values and other none relevant information. I filter this out
using subset which works brilliantly. However, how can I filter using
subset and convert to a time series afterwards. Since after subsetting
there will be 'holes' i.e. missing records. Can a ts object deal with
missing records? If so, how? Just point me to a document. I can and will
put in the work to figure it out myself.

Thank you!
Alex van der Spek