title: Converting nested list to dataframe
body: <p>The goal is to convert a nested list which sometimes contain missing records into a data frame.  An example of the structure when there are missing records is:</p>
  
  <pre><code>str(mylist)
  
  List of 3
   $ :List of 7
    ..$ Hit    : chr "True"
    ..$ Project: chr "Blue"
    ..$ Year   : chr "2011"
    ..$ Rating : chr "4"
    ..$ Launch : chr "26 Jan 2012"
    ..$ ID     : chr "19"
    ..$ Dept   : chr "1, 2, 4"
   $ :List of 2
    ..$ Hit  : chr "False"
    ..$ Error: chr "Record not found"
   $ :List of 7
    ..$ Hit    : chr "True"
    ..$ Project: chr "Green"
    ..$ Year   : chr "2004"
    ..$ Rating : chr "8"
    ..$ Launch : chr "29 Feb 2004"
    ..$ ID     : chr "183"
    ..$ Dept   : chr "6, 8"
  </code></pre>
  
  <p>When there are no missing records the list can be converted into a data frame using <code>data.frame(do.call(rbind.data.frame, mylist))</code>.  However, when records are missing this results in a column mismatch.  I know there are functions to merge data frames of non-matching columns but I'm yet to find one that can be applied to lists.  The ideal outcome would keep record 2 with NA for all variables.  Hoping for some help.</p>
  
  <p>Edit to add <code>dput(mylist)</code>: </p>
  
  <pre><code>list(structure(list(Hit = "True", Project = "Blue", Year = "2011", 
  Rating = "4", Launch = "26 Jan 2012", ID = "19", Dept = "1, 2, 4"), .Names = c("Hit", 
  "Project", "Year", "Rating", "Launch", "ID", "Dept")), structure(list(
  Hit = "False", Error = "Record not found"), .Names = c("Hit", 
  "Error")), structure(list(Hit = "True", Project = "Green", Year = "2004", 
  Rating = "8", Launch = "29 Feb 2004", ID = "183", Dept = "6, 8"), .Names = c("Hit", 
  "Project", "Year", "Rating", "Launch", "ID", "Dept")))
  </code></pre>