How to convert a list consisting of vector of different lengths to a usable data frame in R?

One liner with plyr

plyr::ldply(word.list, rbind)

try this:

word.list <- list(letters[1:4], letters[1:5], letters[1:2], letters[1:6])
n.obs <- sapply(word.list, length)
seq.max <- seq_len(max(n.obs))
mat <- t(sapply(word.list, "[", i = seq.max))

the trick is, that,

c(1:2)[1:4]

returns the vector + two NAs

Another option is stri_list2matrix from library(stringi)

library(stringi)
stri_list2matrix(l, byrow=TRUE)
#    [,1] [,2] [,3] [,4]
#[1,] "a"  "b"  "c"  NA  
#[2,] "a2" "b2" NA   NA  
#[3,] "a3" "b3" "c3" "d3"

NOTE: Data from @juba's post.

Or as @Valentin mentioned in the comments

sapply(l, "length<-", max(lengths(l)))

You can do something like this :

## Example data
l <- list(c("a","b","c"), c("a2","b2"), c("a3","b3","c3","d3"))
## Compute maximum length
max.length <- max(sapply(l, length))
## Add NA values to list elements
l <- lapply(l, function(v) { c(v, rep(NA, max.length-length(v)))})
## Rbind
do.call(rbind, l)

Which gives :

     [,1] [,2] [,3] [,4]
[1,] "a"  "b"  "c"  NA  
[2,] "a2" "b2" NA   NA  
[3,] "a3" "b3" "c3" "d3"

You could also use rbindlist() from the data.table package.

Convert vectors to data.tables or data.frames and transpose them (not sure if this reduces speed a lot) with the help of lapply(). Then bind them with rbindlist() - filling missing cells with NA.

require(data.table)

l = list(c("a","b","c"), c("a2","b2"), c("a3","b3","c3","d3"))
dt = rbindlist(
  lapply(l, function(x) data.table(t(x))),
  fill = TRUE
)