Add dataframes to each list element - r

Question

I am reading a series of files that end up in a list of dataframes. After doing that, i'm interested in putting some additional information related to each dataframe. So, I want to add to each element of my dataframe list, some additional elements.
My attempt was to actually build the list of "extra stuff" and then try to merge it with the list of dataframes.
Example code:
set.seed(42)
#Building my list of data.frames. In my specific case this is coming from files
A <- data.frame(x=rnorm(10), y=rnorm(10))
B <- data.frame(x=rnorm(10), y=rnorm(10))
ListD <- list(A, B)
names(ListD)<- c("A", "B") #some names to know what is what
#now my attributes. Each data.frame as some properties that i want to keep track of.
newList <- list(A=c("Color"=123, "Date"=321), B=c("Color"=111, "Date"=111))
#My wished output is a list were each element of the list has
#"Color", "Date" and a dataframe
#I tried something like:
lapply(ListD, append, values=newList)

Answer 1

As far as I can tell all you have to do is change you're initialization of ListD to:
ListD <- list(list(A), list(B))
Because the data structure you want is a list of lists - with the inner lists holding a data.frame and two further attributes. I can't gurantee this is exactly the result you desire but essently this is where your problem is located.

Answer 2

OK, I thought this would be straightforward with mapply, but I can't get the lists to play together well... maybe someone else can. So here's a for solution:
#preallocate list
updatedList <- vector(mode = "list", length = length(ListD))
names(updatedList) <- names(ListD)
for(i in 1:length(updatedList)) {
updatedList[[i]] <- c(ListD[i], newList[[i]])
}
updatedList$A
# $A
# x y
# 1 -0.51690823 0.4521443
# 2 0.97544933 -0.7212561
# 3 0.98909668 -0.2258737
# 4 -1.72753947 -0.7643175
# 5 -1.31050478 -3.2526437
# 6 -0.63845053 1.1263407
# 7 -0.09010858 -0.9386608
# 8 -0.53933869 -0.6882866
# 9 0.54668290 1.7227261
# 10 -0.87948586 -0.2413344
#
# $Color
# [1] 123
#
# $Date
# [1] 321
Alternatively, if you take #Яaffael's suggestion, mapply works, but that will depend how you're building the list from the files in the first place:
ListD <- list(list(A), list(B))
updatedList <- mapply(c, ListD, newList, SIMPLIFY = FALSE)

Answer 3

I used #Яaffael suggestion of a list of lists.
Since changing my list of dataframes is not very easy, because of the way i'm reading them from files, I made the list of lists with the extra data, and then join the dataframes like this:
newList <- list(A=list("Color"=123, "Date"=321), B=list("Color"=111, "Date"=111))
for(n in names(newList)){
newList[[n]]$Dataframe <- ListD[[n]]
}
the structure of my output:
> str(newList)
List of 2
$ A:List of 3
..$ Color : num 123
..$ Date : num 321
..$ Dataframe:'data.frame': 10 obs. of 2 variables:
.. ..$ x: num [1:10] 1.371 -0.565 0.363 0.633 0.404 ...
.. ..$ y: num [1:10] 1.305 2.287 -1.389 -0.279 -0.133 ...
$ B:List of 3
..$ Color : num 111
..$ Date : num 111
..$ Dataframe:'data.frame': 10 obs. of 2 variables:
.. ..$ x: num [1:10] -0.307 -1.781 -0.172 1.215 1.895 ...
.. ..$ y: num [1:10] 0.455 0.705 1.035 -0.609 0.505 ...