Transform list cell in data frame into rows - json

Question

I'm sorry for no code to replicate, I can provide a picture only. See it below please.
A data frame with Facebook insights data prepared from JSON consists a column "values" with list values. For the next manipulation I need to have only one value in the column. So the row 3 on picture should be transformed into two (with list content or value directly):
post_story_adds_by_action_type_unique lifetime list(like = 38)
post_story_adds_by_action_type_unique lifetime list(share = 11)
If there are 3 or more values in data frame list cell, it should make 3 or more single value rows.
Do you know how to do it?
I use this code to get the json and data frame:
i <- fromJSON(post.request.url)
i <- as.data.frame(i$insights$data)
Edit:
There will be no deeper nesting, just this one level.
The list is not needed in the result, I need just the values and their names.

Answer 1

Let's assume you're starting with something that looks like this:
mydf <- data.frame(a = c("A", "B", "C", "D"), period = "lifetime")
mydf$values <- list(list(value = 42), list(value = 5),
list(value = list(like = 38, share = 11)),
list(value = list(like = 38, share = 13)))
str(mydf)
## 'data.frame': 4 obs. of 3 variables:
## $ a : Factor w/ 4 levels "A","B","C","D": 1 2 3 4
## $ period: Factor w/ 1 level "lifetime": 1 1 1 1
## $ values:List of 4
## ..$ :List of 1
## .. ..$ value: num 42
## ..$ :List of 1
## .. ..$ value: num 5
## ..$ :List of 1
## .. ..$ value:List of 2
## .. .. ..$ like : num 38
## .. .. ..$ share: num 11
## ..$ :List of 1
## .. ..$ value:List of 2
## .. .. ..$ like : num 38
## .. .. ..$ share: num 13
## NULL
Instead of retaining lists in your output, I would suggest flattening out the data, perhaps using a function like this:
myFun <- function(indt, col) {
if (!is.data.table(indt)) indt <- as.data.table(indt)
other_names <- setdiff(names(indt), col)
list_col <- indt[[col]]
rep_out <- sapply(list_col, function(x) length(unlist(x, use.names = FALSE)))
flat <- {
if (is.null(names(list_col))) names(list_col) <- seq_along(list_col)
setDT(tstrsplit(names(unlist(list_col)), ".", fixed = TRUE))[
, val := unlist(list_col, use.names = FALSE)][]
}
cbind(indt[rep(1:nrow(indt), rep_out)][, (col) := NULL], flat)
}
Here's what it does with the "mydf" I shared:
myFun(mydf, "values")
## a period V1 V2 V3 val
## 1: A lifetime 1 value NA 42
## 2: B lifetime 2 value NA 5
## 3: C lifetime 3 value like 38
## 4: C lifetime 3 value share 11
## 5: D lifetime 4 value like 38
## 6: D lifetime 4 value share 13