R iterate over columns dataframe

Question

I want to apply statistics to the columns of a dataframe in an iterated fashion:

columns number 1: 'A' represents the tags that I want to discriminate:

for (i in names(dataframe)) {
    i <- as.name(i)
    group1 <- i[A=="locationX"]
    group2 <- i[A!="locationX"]
    p <- wilcox.test(group1,group2,na.action(na.omit))$p.value
}

however, the as.name() is to try to remove the inverted commas from the column names generated by names(dataframe) .

Unfortunately it gives me the error:

Error in i[A == "locationX"] : object of type 'symbol' is not subsettable

I think as.name() is not the right way to do it.

Any clues?

Answer 1

The only way this makes sense if for "A" to be a vector with multiple instances of "locationX" and multiple instance of the converse and for the length of "A" to be the same as the number of rows in "dataframe". If that is the case then something like this might work:

p <- list()
for (i in names(dataframe)) {
   # using as.names not needed and possibly harmful
    group1 <- dataframe[[i]][A == "locationX"]
    group2 <- dataframe[[i]][A != "locationX"]
    p[i] <- wilcox.test(group1,group2,na.action(na.omit))$p.value
}

Note that even if you did not get an error with your code that you would still have been overwriting the "p" every time through the loop.