R help - Sep 2003 - converting dataframe columns to vector and missing values

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

Have you considered:

	  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
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help