Hi:
Here's one approach, converting the sub-data frames to zoo objects:
# Function to convert one of the data frames to a zoo object
makezoo <- function(df) {
require(zoo)
date <- as.Date(df[, 1], format = '%m/%d/%y')
with(df, zoo(freq, date))
}
library(zoo)
# Split the data frame by condition:
tt <- split(x.df[, -2], x.df$cond)
# > str(tt[[1]])
# 'data.frame': 5 obs. of 2 variables:
# $ date: Factor w/ 5 levels "04/01/09","04/02/09",..: 1 2 3 4 5
# $ freq: int 12 11 10 13 6
# Apply the makezoo function to each component of the list tt:
(tser <- lapply(tt, makezoo))
$Fever
04/01/09 04/02/09 04/03/09 04/04/09 04/05/09
12 11 10 13 6
$Rash
04/01/09 04/02/09 04/03/09 04/04/09 04/05/09
6 10 9 10 8
$Respiratory
04/01/09 04/02/09 04/03/09 04/04/09 04/05/09
12 9 6 11 11
# Check that the classes are OK:
> sapply(tser, class)
Fever Rash Respiratory
"zoo" "zoo" "zoo"
You can then do things like plot.ts, for example:
lapply(tser, plot.ts)
HTH,
Dennis
On Wed, Jun 2, 2010 at 8:37 AM, Erin Hodgess <erinm.hodg...@gmail.com>wrote:
> Dear R People:
>
> I have the following data frame:
>
> > x.df
> date cond freq
> 1 04/01/09 Fever 12
> 2 04/02/09 Fever 11
> 3 04/03/09 Fever 10
> 4 04/04/09 Fever 13
> 5 04/05/09 Fever 6
> 6 04/01/09 Rash 6
> 7 04/02/09 Rash 10
> 8 04/03/09 Rash 9
> 9 04/04/09 Rash 10
> 10 04/05/09 Rash 8
> 11 04/01/09 Respiratory 12
> 12 04/02/09 Respiratory 9
> 13 04/03/09 Respiratory 6
> 14 04/04/09 Respiratory 11
> 15 04/05/09 Respiratory 11
> >
>
> I would like to generate 3 time series (or zoo objects or its); one
> for Fever, one for Rash, and one for Respiratory. There are 2
> questions here, please:
> a. How do I generate the series, please?
> b. Which is best, time series, zoo objects, or its objects, please?
>
> Thanks,
> Erin
>
>
> --
> Erin Hodgess
> Associate Professor
> Department of Computer and Mathematical Sciences
> University of Houston - Downtown
> mailto: erinm.hodg...@gmail.com
>
> ______________________________________________
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>
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