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Folks at R help, I can't quite get the panel function to work the way I want within barchart. I guess I'm still not understanding how to piece together multiple panel arguments, especially when "groups" is specified. Example: I want to be able to add the value of "yield" to each section of each bar in this graph: barchart(yield ~ variety | site, data = barley,

I did not find an answer to my question after a quick search using the R search engine so thought I'd ask away: Does any know if there's a function exists to create an interrupted Y axis? What I mean by interrupted Y axis is that part of the Y axis has been removed or excised to permit one to see parts of the data in more detail. Perhaps an example will make this clear. Please go to

I want to use question numbers from my survey data (fake data below) as markers in a scatterplot. I'm using "as.character" to convert question numbers to characters. However, plot truncates the 0 (zero) off of question 10. How can I get the ending zero so I can add questions 11 - 20? # Sample code below Question <- c(1,2,3,4,5,6,7,8,9,10) Performance <-

Since installing R 2.0 I've had the following 2 issues I can't find solutions for. I'm using Windows XP. 1) R 1.9 continues to read my .Rprofile file in my home directory but R 2.0 does not. How do I get R 2.0 to do this? 2) The following function no longer works in R 2.0 but continues to work in R 1.9: getExcel <- function (x) { invisible(require(RODBC)) x <-

Hi, I recently spent quite a bit of time trouble shooting a function that I had written only to discover that the problem I was having was with the comparison operator. I assumed that the following would return TRUE: > testMean <- 82.8 + 0.1 > testMean [1] 82.9 > testMean == 82.9 [1] FALSE Apparently this has to do with deciml places. Look: > newTest <- 82.0 > newTest [1]

Frank uses the term "hierarchical keyword organization" which I agree is a good way to organize a system designed to help users. In fact, this is one reason why I like the R graphics gallery which allows one to quickly find a particular type of plot based on keyword, examine the plot to see if it's close to what's desired, and then get the detailed code to examine or modify for