On Thu, 11 Sep 2008, Kunzler, Andreas wrote:
Dear List,
I ran into some problems with time-series-Data.
Imagine a data-structure where observations (x) of test attendants (i) are made
a four times (q) a year (y). The data is orderd the following way:
I y q x
1 2006 1 1
1 2006 3 1
1 2006 4 1
1 2007 1 1
1 2007 2 1
1 2007 3 1
1 2007 4 1
2 2006 1 1
3 2007 1 1
3 2007 2 1
I am looking for a way to count the attendants that at least have
attendend one time a year. In this case 2 persons, because i=2 has no
observation in 2007.
You might want to turn your data into an actual time series with one
series per attendend and then aggregate. I've written a few short
transformations based on the data above and using the "zoo" package. It's
somewhat lengthy but might give you a few useful pointers.
hth,
Z
## read data
x <- read.table(textConnection("I y q x
1 2006 1 1
1 2006 3 1
1 2006 4 1
1 2007 1 1
1 2007 2 1
1 2007 3 1
1 2007 4 1
2 2006 1 1
3 2007 1 1
3 2007 2 1"), header = TRUE)
## store year/qtr as "yearqtr" object
library("zoo")
x$yq <- as.yearqtr(x$y + (x$q-1)/4)
x <- x[,-(2:3)]
## reshape data into wide format (one series per individual)
x <- reshape(x, timevar = "I", idvar = "yq", direction = "wide")
## turn data into zoo series with zeros in quarters without observation
z <- zoo(as.matrix(x[,-1]), x[,1])
z <- merge(zoo(,seq(from = start(z), to = end(z), by = 0.25)), z)
z[is.na(z)] <- 0
## aggregate from quarterly to annual observations
zy <- aggregate(z, function(x) as.numeric(floor(x)), sum)
## aggregate over individuals
rollapply(zy, 1, function(x) sum(x > 0), by.column = FALSE)
I thought about creating a subset with the duplicate function. But I
can't find a way to control (i) and (y).
subset(data, !duplicated(i[y]))
Thanx so much
Andreas Kunzler
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