What is zoo? I cannot find anything about zoo int he documentation.
I did try as.ts() see below.
Thank you,
Alex van der Spek
> have you tried using zoo and then using the function as.ts()
>
> On Wed, Apr 8, 2009 at 11:56 AM, <am...@xs4all.nl> wrote:
>> Converting dates is getting stranger still. I am coercing a data frame
>> into a ts as follows:
>>
>>
>> tst1<-as.POSIXct("1/21/09 5:01",format="%m/%d/%y %H:%M")
>> tst2<-as.POSIXct("1/28/09 3:40",format="%m/%d/%y %H:%M")
>> tsdat<-as.ts(dat,start=tst1,end=tst2,frequency=1)
>>
>> This generates a ts object. But strangely enough the first column of
>> that
>> matrix starts at the numeric value of 841 counts up to 1139 and then
>> starts at 1 again, only to count up from there. The restart at 1 occurs
>> at
>> the first day "1/21/09" at 10:00:00.
>>
>> What is so special about that time? This phenomenon happens several
>> times
>> in the long file. But the restart count is always a different number.
>> This creates a ramp with some bumps.
>>
>> Can anybody explain this?
>> Thanks in advance,
>> Alex van der Spek
>>
>>
>>> 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 Â 8.2 76 30 282 1060 53 7
>>> 2 1/21/09 5:02 16256 Â 8.3 76 23 282 1059 54 7
>>> 3 1/21/09 5:03 16150 Â 8.4 76 26 282 1059 55 7
>>> 4 1/21/09 5:04 16150 Â 9.0 76 25 282 1051 57 6
>>> 5 1/21/09 5:05 15543 10.4 76 Â 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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>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
> --
> Stephen Sefick
>
> Let's not spend our time and resources thinking about things that are
> so little or so large that all they really do for us is puff us up and
> make us feel like gods. We are mammals, and have not exhausted the
> annoying little problems of being mammals.
>
> -K. Mullis
>
>
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