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
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