similar to: Wishlist: Function 'difftime' to honor 'tzone' attribute (PR#14182)

Hello all, I've 2 strings that representing the start and end values of a date and time. For example, time1 <- c("21/04/2005","23/05/2005","11/04/2005") time2 <- c("15/07/2009", "03/06/2008", "15/10/2005") as.difftime(time1,time2) Time differences in secs [1] NA NA NA attr(,"tzone") [1] "" How can i

Hello all!!! I want to measure the duration of events (given a start and an end time). The catch is that I require the output in calender days. This means: 02-Jan-2011 00:01:00 minus 01-Jan-2011 23:59:00 should be 1 day (although the real time difference is only 2 minutes) My data is the following head(episode.ct) [1] "2009-07-13 13:37:20 CEST" "2009-07-14 07:29:20 CEST"

How can I apply difftime to a vector of sorted dates? I can do this just fine with diff, but difftime doesn't seem to take in a vector. > diff(r$BOOKING_DATE) Works. Great! > difftime(r$MY_DATE, units="days") Error in as.POSIXct(time2) : argument "time2" is missing, with no default Thanks, Bradford [[alternative HTML version deleted]]

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

I have a problem with results from difftime being 1 hour different than expected. 2 examples are given below: datetime <- matrix(data=rbind(c("2012-03-31 21:00:00", "2012-04-01 00:00:00", "2012-04-01 03:00:00", "2012-04-01 06:00:00"), c("2012-10-06 21:00:00", "2012-10-07 00:00:00", "2012-10-07 03:00:00",

I'm new to R and have the following problem with difftime: if I directly assign date/time strings in difftime I get the expected result: > a<-"2010-03-23 10:52:00" > a [1] "2010-03-23 10:52:00" > b<-"2010-03-23 11:53:00" > u2<-as.difftime(c(a,b), format ="%Y-%m-%d %H:%M:%S", units="mins") > u2 Time differences in mins

Thanks, Tim To get the time difference in the proper units, it's as simple as this: difftime(myfileinfo$mtime[2], myfileinfo$mtime[1], units="hours") Cheers, Warren On 11/13/06, Tim Calkins <tcalkins@gmail.com> wrote: > hardly the most efficient way to go, but consider using a substring > function to extract the time bits from your data, then reading them as POSIX

Dear all, according to the Help-page of DateTimeClasses {base} I should be able to do time - z with time date-time objects z a numeric vector (in seconds) or an object of class "difftime". However, on R version 2.6.0 (Windows XP) I get > Sys.time() - as.difftime(c("0:3:20", "11:23:15")) Time differences in mins [1] 1191837998 1191837318

Full_Name: Suharto Anggono Version: 2.8.1 OS: Windows Submission from: (NULL) (125.161.134.206) About PR#14067, now I understand why (Date + difftime) does not use '+.Date'. But, before I understand, it was surprising. The surprise is also reflected in the post "Problem with +(POSIXt, difftime) dispatching -- WAS: How to create sequence of constant time interval" in R-help

Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire

Hello. I get a bit confused by the output from the predict function when used on an object from coxph in combination with p-spline, e.g. fit <- coxph(Surv(time1, time2, status)~pspline(x), Data) predict(fit, newdata=data.frame(x=1:2)) It seems like the output is somewhat independent of the x-values to predict at. For example x=1:2 gives the same result as x=21:22. Does the result span the

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2

To Whomever is Interested, I have spent several days searching the web, help files, the R wiki and the archives of this mailing list for a solution to this problem, but nonetheless I apologize in advance if I have missed something obvious. The problem is this; I have a 5-column data frame with about 4.2 million rows, and want to create a new (and hopefully much smaller) data frame that

Dear all, I would like to have all unique combinations in the following matrix TimeIndex<- rbind (c(1,"Week_of_21_07-29_03"),           c(2,"Thursday_21_03"),           c(3,"Friday_22_03"),           c(4,"Saturday_23_03"),           c(5,"Sunday_24_03"),           c(6,"Monday_25_03"),           c(7,"Tuesday_26_03"),        

time1 = 2008-03-09 time2 = 2010-9-10 How to compute how many years between time1 and time2? Thanks! best [[alternative HTML version deleted]]

For a model I am working on, I have samples organized by year and week of the year. For this model, the data (year and week) comes from the basic sample data, but I require a value representing the amount of time since the sample was taken (actually, for the purpose of the model, it is sufficient to use the number of weeks from the middle of the sample week to the present). What I have found so

Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate

Hi all, I'm just curious how memory management works in R... I need to run an optimization that keeps calling the same function with a large set of parameters... so then I start to wonder if it's better if I attach the variables first vs passing them in (coz that involves a lot of copying.. ) Thus, I do this fn3 <- function(x, y, z, a, b, c){ sum(x, y, z, a, b, c) } fn4 <-