Iteration over 2 lists in R

user_14518614 0
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I would like to do an iteration with 2 lists.

For a single case, I have one dataframe df1 and one vector v1.

My reproducible example as below.

df1 <- data.frame(n1 = c(2,2,0),
                 n2 = c(2,1,1),
                 n3 = c(0,1,1),
                 n4 = c(0,1,1))

v1 <- c(1,2,3)

Now, I calculate an value (ses.value) for each row using this code

x <- (v1 - apply(df1, 1, mean))/apply(df1,1,sd)

Let's say we will have a list of multiple dataframes l1 and a list of vectors l2 (each list has the same number of elements) Now, I would like to run a loop for those lists by using the above code (the element of l1 must go with the element of l2 with the same position).

# 3 dataframes and 3 vectors
df1 <- data.frame(n1 = c(2,2,0), n2 = c(2,1,1), n3 = c(0,1,1), n4 = c(0,1,1))
df2 <- data.frame(n1 = c(1,6,0), n2 = c(2,1,8), n3 = c(0,2,1), n4 = c(0,7,1))
df3 <- data.frame(n1 = c(1,6,0), n2 = c(9,1,5), n3 = c(4,2,1), n4 = c(0,7,2))

v1 <- c(1,2,3)
v2 <- c(2,3,4)
v3 <- c(4,5,6)

# list
l1 <- list(df1,df2,df3)
l2 <- list(v1,v2,v3)

Since my lists are too big, using for loop might be not such a good idea, any suggestions using lapply or something similar?

lapply r for-loop
2 Answers

We can use Map to loop over the corresponding elements of each list and then do the calculation based on OP's code

Map(function(x, y) (y - apply(x, 1, mean))/apply(x,1,sd), l1, l2)

-output

[[1]]
[1] 0.0 1.5 4.5

[[2]]
[1]  1.3055824 -0.3396831  0.4057513

[[3]]
[1] 0.1237179 0.3396831 1.8516402

Also, if the datasets are really big, use dapply from collapse, which is more efficient

library(collapse)
 Map(function(x, y) (y - dapply(x, MARGIN = 1,
     FUN = fmean))/dapply(x, MARGIN = 1, FUN = fsd), l1, l2)
user_37322710

Since your lists apparently are large, you probably could benefit from rowMeans2 and rowSds of the matrixStats package.

library(matrixStats)
Map(\(x, y) (y - rowMeans2(as.matrix(x))) / rowSds(as.matrix(x)), l1, l2)
# [[1]]
# [1] 0.0 1.5 4.5
# 
# [[2]]
# [1]  1.3055824 -0.3396831  0.4057513
# 
# [[3]]
# [1] 0.1237179 0.3396831 1.8516402

Data:

l1 <- list(structure(list(n1 = c(2, 2, 0), n2 = c(2, 1, 1), n3 = c(0, 
1, 1), n4 = c(0, 1, 1)), class = "data.frame", row.names = c(NA, 
-3L)), structure(list(n1 = c(1, 6, 0), n2 = c(2, 1, 8), n3 = c(0, 
2, 1), n4 = c(0, 7, 1)), class = "data.frame", row.names = c(NA, 
-3L)), structure(list(n1 = c(1, 6, 0), n2 = c(9, 1, 5), n3 = c(4, 
2, 1), n4 = c(0, 7, 2)), class = "data.frame", row.names = c(NA, 
-3L)))

l2 <- list(c(1, 2, 3), c(2, 3, 4), c(4, 5, 6))
user_65740380
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