[R] help with time series

[Mike Lawrence]

To seperate the columns, use the "sep" argument in read.table()

mystage <- read.table("C:\\Documents and
Settings\\skfriedman\\Desktop\\R-scripts\\stage.txt", header =
TRUE,sep=',')

On Fri, Jan 30, 2009 at 4:17 PM,  <Steve_Friedman at nps.gov> wrote:
>
> Hello everyone
>
>
> I'm working with R 2.8.1 on a windows  machine
>
> I have a question regarding time series analysis
>
> The first question is how does R expect the input file to be structured?
> I'm working with a *.txt file similar to the abbreviated one here:
>
> Date,stage
> 4/2/1953,7.56
> 4/3/1953,7.56
> 4/4/1953,7.54
> 4/5/1953,7.53
> 4/6/1953,7.5
> 4/7/1953,7.47
> 4/8/1953,7.44
> 4/9/1953,7.41
> 4/10/1953,7.37
> 4/11/1953,7.33
> 4/12/1953,7.3
> 4/13/1953,7.26
> 4/14/1953,7.28
> 4/15/1953,7.28
> 4/16/1953,7.23
> 4/17/1953,7.47
> 4/18/1953,7.59
> 4/19/1953,7.58
> 4/20/1953,7.57
> 4/21/1953,7.56
> 4/22/1953,7.55
> 4/23/1953,7.53
> 4/24/1953,7.51
> 4/25/1953,7.48
> 4/26/1953,7.46
> 4/27/1953,7.5
> 4/28/1953,7.56
>
> The data record is substantially longer - 50 years worth of daily
> hydrologic water stage data  (column 2).
>
> R seems to get confused by the format of this input not knowing what to do
> with the date field, and also deciding to treat everything as a level.
>
> I'm reading the data as follows:
>
> mystage <- read.table("C:\\Documents and
> Settings\\skfriedman\\Desktop\\R-scripts\\stage.txt", header = TRUE)
>
> looking at the data  I get the following:
>
>  mystage[1:4,]
> [1] 4/2/1953,7.56 4/3/1953,7.56 4/4/1953,7.54 4/5/1953,7.53
> 20195 Levels: 1/1/1954,8.72 1/1/1955,8.48 1/1/1956,7.94 1/1/1957,7.88
> 1/1/1958,8.5 ... 9/9/2007,8.84
>>
>
> What I'd like is a time series  with a starting data of April 21, 1953.
> ending December 30, 2008.  data are daily records, so the frequency should
> be 365 (?) not counting leap year nuisances.
>
> So the first question is how should I build the input file to correctly
> import it to a time series with an odd beginning date?
>
> The analysis I'm really trying to get to will involve calculating the mean
> monthly stage, the mean seasonal (aggregated over several months) stage,
> the annual maximum period with a continuous stage greater than 0.
>
> Thanks in advance I will summary solutions.
>
> Much appreciated
>
> Steve
>
> Steve Friedman Ph. D.
> Spatial Statistical Analyst
> Everglades and Dry Tortugas National Park
> 950 N Krome Ave (3rd Floor)
> Homestead, Florida 33034
>
> Steve_Friedman at nps.gov
> Office (305) 224 - 4282
> Fax     (305) 224 - 4147
>
> ______________________________________________
> R-help at 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.
>



-- 
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
www.thatmike.com

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~ Certainty is folly... I think. ~