By the way, note that read.zoo passes the ... arguments to read.table
and so can use the same skip= and nrows= arguments that read.table
uses. These can be used to read in a subset of the rows.
On Thu, Jul 16, 2009 at 10:35 AM, Gabor
Grothendieck<ggrothendi...@gmail.com> wrote:
> There is no such limitation. There is likely a data problem with
> one or more records past the 280th one.
>
> Suggest you remove the first 280 and then divide the remaining
> in half and try each half and keep dividing that way until you have
> located the offending record or records.
>
> On Thu, Jul 16, 2009 at 8:51 AM, Keith<kigio...@gmail.com> wrote:
>> Thanks Gabor,
>>
>> I tried a little bit, and your example works. However, it seems that
>> the read.zoo has a limitation of records up to around 300 !? I took
>> your suggestion and modified a little bit in order to read from the
>> file which contains about 9000 records:
>>
>> dataTs <- read.zoo("filename.csv", header=TRUE, sep=",", format =
>> "%H:%M:%S %m.%d.%Y", tz = "", strip.white = TRUE)
>>
>> and the R always shows up the message:
>>
>> Error in read.zoo("filename.csv", header = TRUE, sep = ",", format =
>> "%H:%M:%S %m.%d.%Y", :
>> index contains NAs
>>
>> At the beginning, I thought it is the problem of NA, and tried to
>> removed the records with NA. Still, the message appeared until I
>> reduce the number of records to around 280 and it works well with or
>> without NAs.
>>
>> Does anyone has any idea to solve the problem?
>>
>> Regards,
>> Keith
>>
>> On Wed, Jul 15, 2009 at 5:08 PM, Gabor
>> Grothendieck<ggrothendi...@gmail.com> wrote:
>>> Try the zoo package:
>>>
>>> Lines <- "time[sec] , Factor1 , Factor2
>>> 00:00:00 01.01.2007 , 0.0000 , 0.176083
>>> 01:00:00 01.01.2007 , 0.0000 , 0.176417
>>> 11:00:00 10.06.2007 , 0.0000 , 0.148250
>>> 12:00:00 10.06.2007 , NA , 0.147000
>>> 13:00:00 10.06.2007 , NA , 0.144417"
>>>
>>> library(zoo)
>>> library(chron)
>>> z <- read.zoo(textConnection(Lines), sep = ",", header = TRUE,
>>> format = "%H:%M:%S %m.%d.%Y", tz = "", strip.white = TRUE)
>>> plot(z)
>>>
>>> and read the three vignetttes (pdf documents) that come with it.
>>>
>>>
>>> On Wed, Jul 15, 2009 at 10:07 AM, Keith<kigio...@gmail.com> wrote:
>>>> Hello everyone,
>>>>
>>>> I am just a tyro in R and would like your kindly help for some
>>>> problems which I've been struggling for a while but still in vain.
>>>>
>>>> I have a time-series file (with some missing value ) which looks like
>>>>
>>>> time[sec] , Factor1 , Factor2
>>>> 00:00:00 01.01.2007 , 0.0000 , 0.176083
>>>> 01:00:00 01.01.2007 , 0.0000 , 0.176417
>>>> [ ... ]
>>>> 11:00:00 10.06.2007 , 0.0000 , 0.148250
>>>> 12:00:00 10.06.2007 , NA , 0.147000
>>>> 13:00:00 10.06.2007 , NA , 0.144417
>>>> [ ... ]
>>>>
>>>> and I would like to do some basic time-series analyses using R. The
>>>> first idea is to plot these time-series events and the main problem
>>>> was the handling of the date/time format in the 1st column. I was
>>>> using the script below to deal with:
>>>>
>>>> data <-
>>>> read.table("file",header=TRUE,sep=",",colClasses=c("character","numeric","numeric"))
>>>> data$time.sec. <- as.POSIXct(data$time.sec.,format="%H:%M:%S %d.%m.%Y")
>>>> dataTs <- as.ts(data)
>>>> plot.ts(dataTs)
>>>>
>>>> Then, the plot showed up with 3 subplots in one plot. The 1st is the
>>>> linear line with the x-axis being just the sequence of orders and
>>>> y-axis being wrong numbers which is completely wrong. The 2nd and the
>>>> 3rd are correct but the x-axis is still wrong. Does anyone know how to
>>>> plot correct Factor1 and Factor2 with respect to the 1st column time
>>>> format? Or, probably should I use some other packages? Besides, how
>>>> can I plot these two time-series data (Factor1 and Factor2) in two
>>>> separate plots?
>>>>
>>>> Best regards,
>>>> Keith
>>>>
>>>> ______________________________________________
>>>> 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.
>>>>
>>>
>>
>
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