similar to: How can I import user-defined missings from Spss?

I don't use SPSS but following through on your detective work can provide the likely answer. First note that both date numbers are evenly divisible by the number of seconds in a day, i.e. 24*60*60. This suggests that these numbers are seconds since some origin. Since we know "2003/02/11" corresponds to 13264300800 we deduce that the origin must be spss.orig <-

Hi, How can I import user-defined missings from Spss? It works for me to import spss datasets via library(foreign) with read.spss or via library Hmisc by (spss.get). But no matter which way I do import the data, user-defined missings from Spss are always lost. (it makes no difference if there are a single value, a range, or any combination of them. They are always ignored). Is there any way in

R helpers I am getting to grips with R but came across a small problem today that I could not fix by myself. I have 3 text files, each with a single column of data. I read them in using: myData1<-scan("C:/Program Files/R/myData1.txt") myData2<-scan("C:/Program Files/R/myData2.txt") myData3<-scan("C:/Program Files/R/myData3.txt") I wanted to produce a

I can run one-sample t-test on an array, for example a matrix myData1, with the following apply(myData1, 2, t.test) Is there a similar fashion using apply() or something else to run 2-sample t-test with datasets from two groups, myData1 and myData2, without looping? TIA, Gang

Hello I have dataframes. mydata1 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 07:00:00 ","2005-05-25 19:00:00","2005-06-25 07:00:00","2005-06-25 19:00:00 ","2005-07-25 07:00:00","2005-8-25 19:00:00")) or mydata2 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 00:00:00 ","2005-05-25

Dear users, I have a double for loop that does exactly what I want, but is quite slow. It is not so much with this simplified example, but IRL it is slow. Can anyone help me improve it? The data and code for foo_reg() are available at the end of the email; I preferred going directly into the problematic part. Here is the code (I tried to simplify it but I cannot do it too much or else it

I'm using ks.test (mydata, dnorm) on my data. I know some of my different variable samples (mydata1, mydata2, etc) must be normally distributed but the p value is always < 2.0^-16 (the 2.0 can change but not the exponent). I want to test mydata against a normal distribution. What could I be doing wrong? I tried instead using rnorm to create a normal distribution: y = rnorm

hi, just having the idea create a simple tcl/tk gui-dialog for different data-file formats i get starting problems and it would be nice get some tips/tricks from experienced tcl/tk user in R ! tt <- tktoplevel() label.widget <- tklabel(tt,text="Decision Tree GUI") button.widget <- tkbutton(tt,text="Select SPSSFile", command=function()

Hi All, I'm a little stumped by the following problem. I've got a dataset with the following structure: idxy ix iy country (other variables) 1 1 1 c1 x1 2 1 2 c1 x2 3 1 3 c1 x3 . . . . . 3739 55 67 c7 x3739 3740 55 68 c7 x3740 where ix and

I know it sounds like a silly question but whenever i click on "save to file" it doesn't save. whenever i use the function attach(___) it doesn't work, and says object can not be found. i have a series of data (0,0,0,1,1) that i need to save, then i want to attach(...) it in another R window. Please help. Thanks -- View this message in context:

Dear useRs, How could I obtain the confidence intervals for the means of my treatments, when my data was fitted to a GLM? I need the CI's for the Poisson and Negative Binomial distributions. Here's what I have: mydata1 <- data.frame('treatments'=gl(4,20), 'value'=rpois(80, 1)) model1 <- glm(value ~ treatments, data=mydata1, family=poisson) means1 <-

hi, know anybody why this happen ? I''m using winedt , the old code saved in an .R call syntax error''s. Curious is, when i''m type below the same code , it works ??? ...imho a print type problem, what i''m never before observed and can''t recognize with my eyes ? P.S. R.1.6.1 /w2k thanks for advance & regards,christian >>getfile <-

Hi I am really new using R, so this is really a beginner stuff! I created a very small data set on excel and then converted it to .csv file. I am able to open the data on R using the command "read.table ("mydata1.csv", sep=",", header=T)" and it just works fine. But when I want to work on the data (e.g. calculate the mean of variable "X") R says

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R,

Hello, does anyone know of a quick way to create a data frame "like" another, but with more rows? What I'd like to do is this: if mydata is a data.frame like a b c 1 TRUE yes 2 FALSE no 3 TRUE yes I'd like to get mydata2 with the same column names and column types, but without the values and with more rows. All I could think of was to manually do

you could try mapply mydata2<-mapply("[", mydata, lapply(mydata, function(x) !x %in% A)) mydata2[[1]]<-A #to replace the obviously deleted elements of "A" mydata2 mydata2[[1]] mydata2[[2]] mydata2[[3]] mydata2[[4]] Stefano -----Messaggio originale----- Da: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]Per conto di jastar

Hi, I have a problem. Please, look at example and try to help me!! > A<-c("aaa","bbb","ccc","ddd","eee") > B<-c("vvv","ooo","aaa","eee","zzz","bbb") > C<-c("sss","jjj","ppp","ddd") > D<-c("bbb","ccc")

Hi all, I am trying to understand Writing R Extension... Section 1.1.5, data: I include two datasets in a package, one using 'save', the other using 'write.table': --- 8< ---- myData1 <- data.frame(x=1:10) write.table(myData1,file="myData1.txt") myData2 <- data.frame(x=2:10) save(myData2,file="myData2.Rdata") --- 8< ---- Then R CMD check aks me to

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R,

Hello, I am attempting to train a random forest model using the randomForest package on 500,000 rows and 8 columns (7 predictors, 1 response). The data set is the first block of data from the UCI Machine Learning Repo dataset "Record Linkage Comparison Patterns" with the slight modification that I dropped two columns with lots of NA's and I used knn imputation to fill in other gaps.