R获取列表中每个第n个元素的行平均值

Question

I have a nested list and I want to get the mean of one particular variable inside the list.

When my list was not nested, it was simple to do, but I am not sure how to change my code now that there are multiple elements of different sizes str of list:

> str(means2)
List of 1
 $ :List of 2
  ..$ :'data.frame':    12 obs. of  2 variables:
  .. ..$ means        : num [1:12] 465063 355968 76570 542873 854570 ...
  .. ..$ variablenames: chr [1:12] "NumberOfPassengers" "FareClass" "TripType" "JourneyTravelTime" ...
  ..$ :'data.frame':    12 obs. of  2 variables:
  .. ..$ means        : num [1:12] 449490 359997 67899 602895 967327 ...
  .. ..$ variablenames: chr [1:12] "NumberOfPassengers" "FareClass" "TripType" "JourneyTravelTime" ...

I was using this code

testdf=as.data.frame(rowMeans(simplify2array(sapply(means2,"[[",1))))

I am just not sure how to change this code to match the fact the means I am obtaining are from the 2nd element and not the first(only) element.

Thanks for any help

example: edited: example had an error

Answer 1

Based on the str of the nested list for 'means2', this should work

unlist(lapply(means2, function(x) rowMeans(do.call(cbind, sapply(x, "[", 1)))))

---

As there is only a single outer list , we can extract it using [[ , loop over the list elements get the first column as vector, get the elementwise sum with Reduce and divide by the length of the list (in the example it is 2).

Reduce(`+`, lapply(means2[[1]], `[`, 1))/2

Or after extracting the list elements, cbind it and do a rowMeans

rowMeans(do.call(cbind,lapply(means2[[1]], `[`, 1)))

data

means2 <- list(list(data.frame(means = 1:5, variablenames = letters[1:5]),
        data.frame(means = 11:15, variablenames = letters[6:10])) )