You can use sapply
:
res <- sapply(ls(pattern = "store_"), function(x) {
tmp <- get(x)$TOTAL_TRAV
c(mean = mean(tmp), SD = sd(tmp))
})
This will return a matrix. Columns represent store IDs. The two rows contain mean and standard deviation.
You can transform this matrix to a (transposed) data frame with
as.data.frame(t(res))
Here, the two columns contain mean and standard deviation. The row names represent store IDs.