I have a loop to read in a series of .csv files
for (i in 1:3)
{
nam <- paste0("A_tree", i)
assign(nam, read.csv(sprintf("/Users/sethparker/Documents/%d_tree_from_data.txt", i), header = FALSE))
}
This works fine and generates a series of files comparable to this example data
A_tree1 <- data.frame(cbind(c(1:5),c(1:5),c(1:5)))
A_tree2 <- data.frame(cbind(c(2:6),c(2:6),c(2:6)))
A_tree3 <- data.frame(cbind(c(3:10),c(3:10),c(3:10)))
What I want to do is add column names, and populate 2 new columns with data (month and model run). My current successful approach is to do this individually, like this:
colnames(A_tree1) <- c("GPP","NPP","LA")
A_tree1$month <- seq.int(nrow(A_tree1))
A_tree1$run <- c("1")
colnames(A_tree2) <- c("GPP","NPP","LA")
A_tree2$month <- seq.int(nrow(A_tree2))
A_tree2$run <- c("2")
colnames(A_tree3) <- c("GPP","NPP","LA")
A_tree3$month <- seq.int(nrow(A_tree3))
A_tree3$run <- c("3")
This is extremely inefficient for the number of _tree
objects I have. Attempts to modify the loop with paste0()
or sprintf()
to incorporate these desired manipulations have resulted in Error: target of assignment expands to non-language object
. I think I understand why this error is appearing based on reading other posts (Error in <my code> : target of assignment expands to non-language object). Is it possible to do what I want within my for loop? If not, how could I automate this better?