Converting nested list (unequal length) to data frame [duplicate]

Question

I have a nested list; for some indices, some variables are missing.

[[1]]
    sk   ques   pval 
  "10" "sfsf" "0.05" 

[[2]]
    sk   ques   pval   diff 
 "24" "wwww" "0.11"  "0.3" 

[[3]]
    sk   ques   pval   diff    imp 
  "24" "wwww" "0.11"  "0.3"    "2" 

How can I convert this to data frame, where for the first row, data$diff[1] = NA? Above case will be data frame with 5 variables and 3 observations.

The number of variables in the data frame will be number of unique names in list elements, and missing values inside the list will be replaced with NA's.

Thank you,

EDIT : Data format

list(structure(c("10", "sfsf", "0.05"), .Names = c("sk", "ques", 
"pval")), structure(c("24", "wwww", "0.11", "0.3"), .Names = c("sk", 
"ques", "pval", "diff")), structure(c("24", "wwww", "0.11", "0.3", 
"2"), .Names = c("sk", "ques", "pval", "diff", "imp")))

Answer 1

We get the length of list element ('indx') by looping with sapply. In the recent version of R, we can use lengths to replace the sapply(.., length) step. We change the length of each element to the max length from the 'indx' (length<-) and thereby pad NA values at the end of the list elements with length less than the max length. We can rbind the list elements, convert to data.frame and change the column names.

 indx <- sapply(lst, length)
 #indx <- lengths(lst) 
 res <- as.data.frame(do.call(rbind,lapply(lst, `length<-`,
                          max(indx))))

 colnames(res) <- names(lst[[which.max(indx)]])
 res
 # sk ques pval diff  imp
 #1 10 sfsf 0.05 <NA> <NA>
 #2 24 wwww 0.11  0.3 <NA>
 #3 24 wwww 0.11  0.3    2

data

 lst <- list(structure(c("10", "sfsf", "0.05"), .Names = c("sk", "ques", 
 "pval")), structure(c("24", "wwww", "0.11", "0.3"), .Names = c("sk", 
 "ques", "pval", "diff")), structure(c("24", "wwww", "0.11", "0.3", 
 "2"), .Names = c("sk", "ques", "pval", "diff", "imp")))