Assuming the date as id is the first column followed by 23 values, try
the read.reps function found here:
http://www.mail-archive.com/r-help@r-project.org/msg92123.html
like this:
DF <- read.csv("myfile", as.is = TRUE)
read.reps(DF, 23)
On Wed, Apr 21, 2010 at 2:24 PM, Idgarad wrote:
> I have
I'm guessing that you are using the words "table" and
"list" to mean "data frame". If that's the case, something
like this might get you started:
dfnew = reshape(Test1,varying=list(paste('Hour',1:23,sep='')),
timevar='Hour',idvar='Date',direction='long')
dfnew = dfnew[order(dfne
I have a series of tables, one for each environment indicating a date (row)
and a sample at each hour of the day (0 to 23)
Test1 Table:
Date,Hour1,Hour2,...Hour23
1/1/10,123,123,...,123
I would like to model this as a time series but how can I translate the
table into a list such that I can get:
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