I have a list (my.list) that looks like this:
$S1
Study_ID B C D
1 100 3.4 C1 0.9124000
2 100 1.5 PTA NA
3 200 1.8 C1 0.5571429
4 200 2.1 PTA 0.7849462
5 300 3.2 C1 0.3271900
6 300 1.4 PTA NA
7 400 5.6 C1 0.8248200
8 400 9.3 PTA 0.2847020
$S2
Study_ID B C D
1 100 0.15 C1 0.9124000
2 100 0.70 PTA NA
3 200 0.23 C1 0.5571429
4 200 0.45 PTA 0.7849462
5 300 0.91 C1 0.3271900
6 300 0.78 PTA 0.6492000
7 400 0.65 C1 0.8248200
8 400 0.56 PTA NA
I would like to create a data frame that consists of only the average of column 'B' in the lists.
My desired output would look something like this:
Average
1 2.1
2 1.2
3 0.5
4 1.5
5 1.9
6 2.1
7 3.6
8 5.9
How can I go about doing this?
Reproducible Data:
my.list <- structure(list(S1 = structure(list(Study_ID = c(100, 100, 200, 200, 300,300,400,400), B = c(3.4, 1.5, 1.8, 2.1, 3.2, 1.4, 5.6, 9.3), C = c("C1", "PTA", "C1", "PTA", "C1", "PTA","C1", "PTA"), D = c(0.9124, NA, 0.5571429, 0.7849462, 0.32719, NA, 0.82482, 0.284702)), .Names = c("Study_ID", "B", "C", "D"), class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8")), S2 = structure(list(Study_ID = c(100, 100, 200, 200, 300,300,400,400), B = c(0.15, 0.7, 0.23, 0.45,0.91, 0.78, 0.65, 0.56), C = c("C1", "PTA", "C1", "PTA", "C1", "PTA", "C1", "PTA"), D = c(0.9124, NA, 0.5571429, 0.7849462, 0.32719,0.6492, 0.82482, NA)), .Names = c("Study_ID", "B", "C","D"), class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8"))), .Names = c("S1", "S2"))
We could extract the 'B" column from the list and use Reduce to get the elementwise sum and divide by the length of the list
Reduce(`+`, lapply(my.list, `[[`, "B"))/length(my.list)
Or extract as a matrix and then use rowMeans
rowMeans(sapply(my.list, `[[`, "B"), na.rm = TRUE)