Can't say whether its any faster but read.zoo in the devel version of
zoo can do this using the split= argument where split=2 in the
example below says to split it into time series defined by the
second column.
Lines <- '"t" "id" "x"
1 "a" -1.71941257904109
1 "b" 1.33629503083329
1 "c" 1.61337372076629
2 "c" 1.34439849784170
2 "b" 0.167475882421629
2 "d" -0.447868997085645
2 "e" -0.592497543309015
3 "b" 0.952268366091281
3 "a" -0.532804723204108
3 "e" -1.20064709102901
4 "a" 2.10892119828104
4 "b" -0.0550779510849278
4 "d" 1.98864434974374
5 "b" 1.59258204616364
5 "c" 0.65185104628371'
library(zoo)
source("http://r-forge.r-project.org/plugins/scmsvn/viewcvs.php/*checkout*/pkg/R/read.zoo.R?rev=588&root=zoo";)
z <- read.zoo(textConnection(Lines), header = TRUE, split = 2)
See the three zoo vignettes and the zoo help pages for more on zoo.
On Wed, Jul 1, 2009 at 1:35 PM, Young Cho<young.s...@gmail.com> wrote:
> Hi, thanks everyone for any help in advance.
>
> I found myself dealing with a tabular time-series data formatted each row
> like [ time stamp, ID, values]. I made a small examples:
>
> X = data.frame(t=c(1,1,1,2,2,2,2,3,3,3,4,4,4,5,5),id =
> c('a','b','c','c','b','d','e','b','a','e','a','b','d','b','c'))
> X$x = rnorm(15)
>
> 't' is time stamp, 'id' is identifier, 'x' is time series values. They are
> not necessarily ordered and have sometimes missing values. In order to do
> any analysis, I used to convert this type of data into a matrix form :
>
> Y = matrix(NA,length(unique(X$id)),length(unique(X$t)))
> rownames(Y) = sort(unique(X$id))
> colnames(Y) = sort(unique(X$t))
> for(i in 1:nrow(Y)){
> xi = X[ X$id == rownames(Y)[i], ]
> Y[i, match(xi$t, colnames(Y)) ] = xi$x
> }
>
> Then, run any R operations on Y. Now, this conversion gets very painfully
> slow as my data gets substantially larger. I was wondering if there is some
> better ways to convert a table like 'X' into a matrix like 'Y', or even
> better ways to re-format data, not necessarily matrix form.
>
> Young
>
> [[alternative HTML version deleted]]
>
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>
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