similar to: Read.table - Less rows than original data

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,

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

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

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

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

I'm trying to convert data from character to numeric. I've imported data as a csv file, I'm assuming that the import is a database - are all the columns in a database considered "vectors" and that they can be operated on individually Therefore I've tried the following mydata <- as.numeric(mydata$apples) when i then look at mydata again the named column is still

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

Dear All, I have a dissimilarity matrix which I happily convert to a distance object by running: X <- as.dist(Y) and I can happily now run either hclust(X) or agnes(X). So that the various bits of output are labelled correctly I would dearly like to be able to give names to the columns and rows of X, as would happen if I ran: mydata<-read.table("clipboard",header=T)

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

Hi, 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 to find out if any value was user-defined missing

Hello fellow R's, I?ve been learning to use the ggplot2 library, and after a full day of work I still have a couple of basic questions. Here is an example: mydata=data.frame(x=runif(20),y=runif(20),n=runif(20)) mydata2=data.frame(x=c(0.4,0.6,0.5),y=c(0.4,0.4,0.6)) ggplot(mydata, aes(x, y)) + geom_point(aes(size = n)) + geom_polygon(data=mydata2,aes(x,y,alpha=0.5)) In this plot, the

Hi all, So I think I have seen some similar questions to mine when I searched the archives, but have not seen any concrete answers and was wondering if any one could help. I have been trying to use R's aov() function to analyze my data. I have a 3 x 4 x 2 repeated measures design. All of the IVs are within subjects. I do also have missing values (unequal N), as I have to remove

Dear all, I run a loop wrapped in try(), and for each of the rows where "try-error" is true I want to fill that row with NA (at the moment it is omitted). So I would expect to get a dataframe with 1000 rows some of which would be empty, but instead I get a dataframe with 995 rows. In this case missing 5 rows were omitted. Any suggestions? Thanks, Olga ----------------

Dear all, Does someone know an R function implementing the method of Sison and Glaz (1995) (see full ref below) for computing Simultaneous confidence intervals for multinomial proportions? As alternative method, I think to boostrap the mean of each proportion and get in that way confidence interval of the mean. I observed 21 times a response that could be one out of 8 categories

Hi the list, Some rumour (!) say that is it possible to prepare some tests for checking our code using .Rin and .Rout. It seems to be a very good practice, but I did not manage to find information on it. So does someone know how it works ? What are we suppose to write in Rin ? More precisely : - I have a package myPack.r in directories ~/myR/myPack/R/ - I create the directory

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")

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 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 studied in tank prey fish behavior. Using the design described below (and R code), I want to test the effects of both habitat and predator (and interaction) on prey fish's vertical distribution, which was recorded (with repeated measures) as a categorical variable. I found that package mlogit might fit to my need but I don't know how to specify my complex design in the

Hi all, I would like to check if a string contains "." in it. If yes, I would like to know the position of "." in the string. Eg: X<-"NM1236.3" In above example, "." is at position 7. I tried functions grep() and match(). It seems they couldn't detect ".". Thanks in advance for your help, Sityee [[alternative HTML version deleted]]