R help - Jun 2002 - lattice and dates (correcting e-mail formatting glitch - sorry!!)

Hi

I'm fairly new to R and the list, so please take
what I say accordingly!

Far as I can see, strptime gives you a string in some
specified format. In order to do any kind of
numerically-based modelling with that, you need to
obtain a number to work with. One way to do this is by
getting the time with Sys.time() instead and coercing
it to a number using as.integer():
 > as.integer(Sys.time())

I dare say you could also set up a structure in which
there are both numeric and string fields, do your
modelling with the former and labelling with the
latter:
> now=Sys.time() 
> numero= as.integer(now) 
> dateo= format(now, "%a, %b %d, %Y") 
> timeo= format (now, "%X") 
> item=list(numeric=numero, strings=c(timeo,dateo))
This seems to do the trick, and gives you a list with
values that look like this.
> item
 $numeric [1] 1025176725
 $strings [1] "12:18:45" "Thu, Jun 27, 2002"

 I guess many of us might also choose to normalize the
$numeric by subtracting some suitable base date/time
from each reading of numero, which appears to be the
number of seconds since 1/1/70, to give a more useful
time origin!

Nick Sherrard, PhD
reduplicativeblending at yahoo.co.uk
______________________________________________________
Subject: [R] lattice and dates I've got some data that
is recorded at various times during the day. I create
a time stamp is created from date and time strings
like this: > timestamp <- strptime( paste( datestring,
timestring), "%D %X" ) Then I'd like to use lattice to
plot the time dependence by doing something like >
xyplot( value ~ timestamp | subject ) This fails with
Error in as.double.default(x) : (list) object cannot
be coerced to vector type 14 In addition: Warning
message: Both x and y should be numeric in: xyplot(
value ~ timestamp | subject ) I was sure I saw
something like this on r-help recently, but I can't
seem to track it down now. Can anyone help me out?
Thanks, Mike - -- Michael A. Miller mmiller3 at iupui.edu
Imaging Sciences, Department of Radiology, IU School
of Medicine - 



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Hi Nick,

Thanks for the suggestions.  At the suggestion of another reader,
I've settled on using the chron package (from CRAN).  I'll append
an example for those who are interested.

Mike

-- 
Michael A. Miller                               mmiller3 at iupui.edu
  Imaging Sciences, Department of Radiology, IU School of Medicine




df.data <- read.table('df.log')
names(df.data) <- c( 'datestamp', 'timestamp', 'dev',
'size',
                     'used', 'available', 'percentage',
'path')

library(chron)
library(lattice)

print( df.data$datestamp )
print( df.data$timestamp )

df.data$date <- chron( dates=as.vector(df.data$datestamp), 
                       times=times(df.data$timestamp) )
#df.data$date <- strptime( paste( df.data$datestamp, df.data$timestamp),
"%D %X" )
print( df.data$date )

pos <- pretty( as.numeric( df.data$date ) )
lab <- as.character( dates(df.data$date) )
xyplot( used/size ~ as.numeric(date) | path, data=df.data,
        scales = list(x = list(at = pos, labels = lab )))


sample df.log:
06/25/02 13:48:58 node2:/data2          67638296  48221224  15981176  76% /data2
06/26/02 15:59:23 node2:/data2          67638296  52972176  11230224  83% /data2
06/27/02 12:07:45 node2:/data2          67638296  56713248   7489152  89% /data2
06/25/02 13:48:58 node3:/data3          67638296  50150280  14052120  79% /data3
06/26/02 15:59:23 node3:/data3          67638296  54900656   9301736  86% /data3
06/27/02 12:07:45 node3:/data3          67638296  56775680   7426720  89% /data3
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