[R] converting dataframe columns to vector and missing values
Spencer Graves
spencer.graves at pdf.com
Fri Sep 12 19:19:52 CEST 2003
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
>
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