R for loop to calculate wilcox.test - r

Question

I am trying to write a code that would automatically calculate Wilcoxon test p-value for several comparisons.
Data used: 2 data sets with the same information representing two groups of participants completed the same 5 tasks which means that the each table contains 5 columns (tasks) and X rows with tasks scores.
data_17_18_G2 # first data set (in data.table format)
data_18_20_G2 # second data set (in data.table format)
Both data sets have identical names of column which are to be used in the W-test the next way:
wilcox.test(Group1Task1, Group2Task1, paired = F)
wilcox.test(Group1Task2, Group2Task2, paired = F)
and so on.
The inputs (e.g., Grou1Task1) are two vectors of task scores (the first one will be from data_17_18_G2 and the other one from data_18_20_G2
Desired output: a data table with a column of p-values
The problem I faced is that no matter how I manipulated the val1 and val2 empty objects, in the second and the third lines the right size "as.numeric(unlist(data_17_18_G2[, ..i]))" gives a correct output (a numeric vector) but it's left size "val1[i]" always returns only one value from the vector. That gave me the idea that the main problem appeared on the step of creating an empty vector, however, I wasn't able to solve it.
Empty objects:
result <- data.table(matrix(ncol=2))
val1 <- as.numeric() # here I also tried functions "numeric" and "vector"
val2 <- as.numeric()
res <- vector(mode = "list", length = 7)
For loop
for (i in 1:5) {
val1[i] <- as.numeric(unlist(data_17_18_G2[ , ..i]))
val2[i] <- as.numeric(unlist(data_18_20_G2[ , ..i]))
res[i] <- wilcox.test(val1[i], val2[i], paired = F)
result[i, 1] <- i
result[i, 2] <- res$p.value
}
Output:
Error in `[<-.data.table`(`*tmp*`, i, 2, value = NULL) :
When deleting columns, i should not be provided
1: В val1[i] <- as.numeric(unlist(data_17_18_G2[, ..i])) :
number of items to replace is not a multiple of replacement length
2: В val2[i] <- as.numeric(unlist(data_18_20_G2[, ..i])) :
number of items to replace is not a multiple of replacement length
3: В res[i] <- wilcox.test(val1[i], val2[i], paired = F) :
number of items to replace is not a multiple of replacement length
Alternative:
I changed the second and the third lines
for (i in 1:5) {
val1[i] <- as.numeric(data_17_18_G2[ , ..i])
val2[i] <- as.numeric(data_18_20_G2[ , ..i])
res[i] <- wilcox.test(val1[i], val2[i], paired = F)
result[i, 1] <- i
result[i, 2] <- res$p.value
}
And got this
Error in as.numeric(data_17_18_G2[, ..i]) :
(list) object cannot be coerced to type 'double'
which means that the function wilcox.test cannot interpret this type of input.
How can I improve the code so that I get a data table of p-values?

Answer 1

There would appear to be some bugs in the code. I have rewritten the code using the cars dataset as a example.
## use the cars dataset as a example (change with appropriate data)
data(cars)
data_17_18_G2 <- as.data.table(cars)
data_18_20_G2 <- data_17_18_G2[,2:1]
## Fixed code
result <- data.table(matrix(as.numeric(), nrow=ncol(data_17_18_G2), ncol=2))
val1 <- as.numeric()
val2 <- as.numeric()
res <- vector(mode = "list", length = 7)
for (i in 1:ncol(data_17_18_G2)) {
val1 <- as.numeric(unlist(data_17_18_G2[ , ..i]))
val2 <- as.numeric(unlist(data_18_20_G2[ , ..i]))
res[[i]] <- wilcox.test(val1, val2, paired = F)
result[i, 1] <- as.numeric(i)
result[i, 2] <- as.numeric(res[[i]]$p.value)
}
Hope this gives you the output you are after.