x <- Data[!is.na(Data[,n]), n]
Does this do what you want? Vectors, arrays, and data.frame can be indexed by number or by a logical vector -- and by names if such are supplied. In this case, "!is.na(Data[,n])" is a logical vector of length = number of rows of Data.
hope this helps. spencer graves
Bock, Michael wrote:
I am relatively new to R, but very pleased with what I can do with it so far. I am embarrassed to ask what seems like a simple question but I am at my wits end. Basically I have written a function to calculate a bootstrapped statistic on a list of values. The function works perfectly if I can feed it the right data. I am exporting data into R as a dataframe and then assigning each column to the list and running the function use a for loop. The problem is what is the best way to convert the columns to a list. The column names and the number of columns will vary depending on the dataset. I am currently converting the dataframe to a matrix and the assigning each column of the matrix to the list in turn:
#InputData is the dataframe
RunTests <- function (InputData) {
n <- length(InputData)
Chem <- colnames(InputData)
for (i in 1:n){
print (Chem[i])
Data <- data.matrix(InputData)
x <- Data[,n]
na.omit(x)
#print(x)
UCL <- HallBoot(x)
print (UCL)
}
} Although this works some of the time, missing values are not removed. This
is a huge problem as the number of observation is each column is quite
variable. Obviously the na.omit is not working the way I expect. Any help
would be appreciated, including a whole new approach to sending the data to
the HallBoot function.
Michael J. Bock, PhD. ARCADIS 24 Preble St. Suite 100 Portland, ME 04101 207.828.0046 fax 207.828.0062
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