Unpacking and merging lists in a column in data.frame

Here's a full dplyr + tidyr solution, the way I'd tackle it:

library(dplyr)
library(tidyr)

df <- data_frame(
  id = c("1001", "1002","1003", "1004", "1005"), 
  name = c("Joan", "Jane", "John", "Bill", "Tom"), 
  altNames = list(character(0), c("Janie", "Janet", "Jan"), "Jon", "Will", character(0))
)

# Need some way to concatenate a list of vectors with a vectors
# in a "rowwise" way
vector_c <- function(...) {
  Map(c, ...)
}

df %>% 
  mutate(
    names = vector_c(name, altNames),
    altNames = NULL,
    name = NULL
  ) %>% 
  unnest(names)
#> Source: local data frame [10 x 2]
#> 
#>      id names
#> 1  1001  Joan
#> 2  1002  Jane
#> 3  1002 Janie
#> 4  1002 Janet
#> 5  1002   Jan
#> 6  1003  John
#> 7  1003   Jon
#> 8  1004  Bill
#> 9  1004  Will
#> 10 1005   Tom

Most of the hard work is done by tidyr::unnest(): it's designed to take data frame with a list-column and unnest it, repeating the other columns as needed.

Here's a possible data.table approach

library(data.table)
setDT(dat)[, .(name = c(name, unlist(altNames))), by = id]
#       id  name
#  1: 1001  Joan
#  2: 1002  Jane
#  3: 1002 Janie
#  4: 1002 Janet
#  5: 1002   Jan
#  6: 1003  John
#  7: 1003   Jon
#  8: 1004  Bill
#  9: 1004  Will
# 10: 1005   Tom

A base R version (using the df added by @rawr)

with(df, {
    ns <- mapply(c, name, altNames)
    data.frame(id = rep(id, times=lengths(ns)), name=unlist(ns), row.names=NULL)
})
#     id  name
#1  1001  Joan
#2  1002  Jane
#3  1002 Janie
#4  1002 Janet
#5  1002   Jan
#6  1003  John
#7  1003   Jon
#8  1004  Bill
#9  1004  Will
#10 1005   Tom