similar to: creating a data frame from a list

Dear all, I have a list with three (named) numeric vectors: > lst = list(a=c(A=1,B=8) , b=c(A=2,B=3,C=0), c=c(B=2,D=0) ) > lst $a A B 1 8 $b A B C 2 3 0 $c B D 2 0 Now, I'd love to use this list to create the following data frame: > dtf = data.frame(a=c(A=1,B=8,C=NA,D=NA), + b=c(A=2,B=3,C=0,D=NA), + c=c(A=NA,B=2,C=NA,D=0) ) > dtf a b

Hi, I have two data frames. One is like > dtf = data.frame(y=c(rep(2002,4), rep(2003,5)), + m=c(9:12, 1:5), + def=c(.74,.75,.76,.78,.80,.82,.85,.85,.87)) and the other dtf2 = data.frame(y=rep( c(2002,2003),20), m=c(trunc(runif(20,1,5)),trunc(runif(20,9,12))), inc=rnorm(40,mean=300,sd=150) ) What I want is to divide

Hi all, I have a (hopefully) simple newbie-level question.   # I have data like this: dtf <- data.frame(read.table(textConnection("var  value   company  9887.1   company  91117.0   blaah  91.1   etc  11   etc  97111"), header=TRUE))   # I would like to have output like this (the index number may vary): var  value.1 value.2 company 9887.1 91117.0 blah  91.1 NA etc 11 97111   # I

This continues the message "data.frame within a function (PR#9294)" that was posted on 2006/10/12. Duncan Murdoch kindly replied. I'm using the current version R 2.4.0, but the same issue exists. Just copy and paste the following code under R, and compare the output of f1() and f2() and the output of f3() and f4(). Does anybody have any idea? Thanks.

Hi there, From the vector X of integers, X = c(11999, 122000, 81997) I would like to make these two vectors: Z= c(1999, 2000, 1997) Y =c(1 , 12 , 8) That is, each entry of vector Z receives the four last digits of each entry of X, and Y receives "the rest". Any suggestions? Thanks in advance, Dimitri [[alternative HTML version deleted]]

Hi everybody! I'm creating an object of a S4 class that has two slots: ListExamples, which is a list, and idx, which is an integer (as the code below). Then, I read a data.frame file with 10000 (ten thousands) of lines and 10 columns, do some pre-processing and, basically, I store each line as an element of a list in the slot ListExamples of the S4 object. However, many operations after this

I have a model: mod1<-lmer( x ~ (1|rtr)+ trth/(1|cs) , data=dtf) # Here, cs and rtr are crossed random effects. cs 1-5 are of type TRUE, cs 6-10 are of type FALSE, so cs is nested in trth, which is fixed. So for cs I should get a fit for 1-5 and 6-10. This appears to be the case from the random effects: > mean( ranef(mod1)$cs[[1]][1:5] ) [1] -2.498002e-16 > var(

Dear R-developers, I would like to suggest a 'method' slot for format.ftable() (see an adjusted 'format.ftable()' below, taken from the source of R-2.15.2). At the moment, format.ftable() contains several empty cells due to the way the row and column labels are printed. This creates problems (= unwanted empty columns/rows) when converting an ftable to a LaTeX table; see an

Dear R-help, I wonder if you could give me some suggestions in how to do a union join of two data frames as follow: -> union join the common column, and insert a 0 if one is missing. I made a function to perform the following, and I know it may not that quite welly written, but it works. Any suggestions are welcome, many thanks. Anthony > q1 =

Hi, Suppose I I wish to run lm( y ~ x + z + log(w) ) where w assumes non-negative values. A problem arises when w=0, as log(0) = -Inf, and R doesn't accept that (as it "accepts" NA). Is there a way to tell R to do with -Inf the same it does with NA, i.e, to ignore it? ( Otherwise I have to do something like w[w==0] <- NA which doesn't hurt, but might be a bit

Hello, I was wondering if there is a function in R that imports tables directly from a HTML document. I know there are functions (say, getURL() from {RCurl} ) that download the entire page source, but here I refer to something like google document's function importHTML() (if you don't know this function, go check it, it's very useful). Anyway, if someone of something that does this

I put the idea below into a function that gives nicer looking results. Here's the new code: dupnames <- function(path = ".") { Rfiles <- pkgload:::find_code(path) allnames <- data.frame(names=character(), filename=character(), line = numeric()) result <- NULL for (f in Rfiles) { exprs <- parse(f, keep.source = TRUE) locs <-

Hi, I wonder if someone has already figured out a way of making summary(mylm) # where mylm is an object of the class lm() to print the "(Intercept)" at the last line, rather than the first line of the output. I don't know about, say, biostatistics, but in economics the intercept is usually the least interesting of the parameters of a regression model. That's why, say, Stata

Can anyone tell me what is wrong in this picture with error output: rsync -nvviirp --inplace harry@harvey:/cygdrive/c/Documents\ And\ Settings ./docs_settings_$(dtf) opening connection using ssh harvey -l harry rsync --server --sender -vvnpr --inplace . "/cygdrive/c/Documents And Settings" harry@harvey's password: protocol version mismatch -- is your shell clean? (see the rsync

Pd: Perdón por el duplicado de mensaje, se me olvido poner el asunto al anterior y me han surgido nuevas consultas. Buenos días, llevo unos dias peleando para realizar una consulta con INSERT en Windows SQL. He probado varios paquetes de R y con ninguno lo he conseguido. Ahora mismo estoy probando con DBI y odbc. Probé con dbSendStatementy al ejecutar la consulta:

Hi there, I am trying to export a regression output to Latex. I am using the xtable function in the xtable library. Doing myfit <- lm(myformula, mydata) print.xtable(xtable(myfit), file="myfile") only returns the estimated coefficients and the correspondent standard erros, t-statiscs and p-values. But I wish to get a bit more, say, the number of observations used in the

Dear All, I have a problem in making a matrix from a data. I did a summary data from a big data frame using (ddply), the resulting table is like that: Site.No Plant.Name Cover.Percentage 1 XXX 15 1 YYY 20 2 XXX 18 2 YYY 21 3 XXX 14 3

Hi there, I am trying to compute Gini coefficients for vectors containing income classes. The data I possess look loke this: yit <- c(135, 164, 234, 369) piit <- c(367, 884, 341, 74 ) where yit is the vector of income classes, and fit is the vector of associated frequencies.(This data is from Rustichini, Ichino and Checci (Journal of Public Economics, 1999) ). In ineq pacakge, Gini( )

Dear all, A few weeks ago, I asked this list why small Stata files became huge R files. Thomas Lumley said it was because "Stata uses single-precision floating point by default and can use 1-byte and 2-byte integers. R uses double precision floating point and four-byte integers." And it seemed I couldn't do anythig about it. Is it true? I mean, isn't there a (more or less

Hi, x and y are (numeric) vectors. I wonder if one of the following is more efficient than the other: x%*%y or sum(x*y) ? Thanks, Dimitri Szerman