search for: datafrs

Sorry I'm having one of those moments where I can't find the answer but I bet its obvious... I'm outputting my results to a file using sink() Is there a command simillar to php's echo command that would allow me to add some text to that file ie: dataFr$a = 1:10 dataFr$b = 2*1:10 sink ("filepath/filename.txt", split=T) #Show number of entries in vector a table

Apologies if this is in (one of the many) manuals somewhere... Trying to switch to R from other stats programs. Basically, I have a large data table I've dumped from a DB, some of the values which are nulls '-' which I've converted to zeros. I've read it in using read.table fine. I want R to ignore the zero values when graphing or doing various other calculations. Is

I've passed a data.frame as an input into a function which does some plotting on a 4x4 matrix of certain parameters within in the data.frame. I'd like to add a small header on top of each plot with the name of the data.frame so that it's clear as I compare these 16 things where each on came from. So far I haven't found the right way to get the name of the data.frame as a string

Windows 2000 R 1.4 I have a split-split plot design that I am analyzing with model <- aov(). I tried using model.tables(model) and it replied "Error: subscript out of bounds." I have monkeyed with it a little, but am wondering if this is indicative of something in particular. Thanks, Hank Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami

Dear R guru's, I'd like to sort the columns of a matrix according to the elements in the first row, and in case of a tie according to the second row, etc. In case of a 3xn matrix woppa, something like colorder _ order(woppa[1,], woppa[2,], woppa[3,]) I just cannot seem to find a way to do this for a variable number of rows, e.g. if woppa has 10 or 15 rows I now manually cut and paste to

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)