code: def parse_docword(filename, vocab_filename):
      """
      Parse a file that's in "docword" format. This consists of a 3-line header
      comprised of the document count, the vocabulary count, and the number of
      tokens, i.e. unique (doc_id, word_id) pairs. After the header, each line
      contains a space-separated triple of (doc_id, word_id, frequency), where
      frequency is the number of times word_id occurred in document doc_id.
  
      This format assumes that documents and words are identified by a positive
      integer (whose lowest value is 1).
      Thus, the first word in the vocabulary file has word_id=1.
  
      2
      272
      5
      1 5 1
      1 105 3
      1 272 5
      2 1 3
      ...
  
      Parameters
      ----------
      filename : str
          The name of the file to parse.
  
      vocab_filename : str
          A list of words that are used for this data set.
  
      Returns
      -------
      out : SArray
          Each element represents a document in bag-of-words format.
  
      Examples
      --------
      >>> textfile = 'https://static.turi.com/datasets/text/docword.nips.txt')
      >>> vocab = 'https://static.turi.com/datasets/text/vocab.nips.txt')
      >>> docs = turicreate.text_analytics.parse_docword(textfile, vocab)
      """
      vocab = _turicreate.SFrame.read_csv(vocab_filename, header=None)[
          "X1"
      ]
      vocab = list(vocab)
  
      sf = _turicreate.SFrame.read_csv(filename, header=False)
      sf = sf[3:]
      sf["X2"] = sf["X1"].apply(
          lambda x: [int(z) for z in x.split(" ")]
      )
      del sf["X1"]
      sf = sf.unpack(
          "X2", column_name_prefix="", column_types=[int, int, int]
      )
      docs = sf.unstack(["1", "2"], "bow").sort("0")["bow"]
      docs = docs.apply(
          lambda x: {vocab[k - 1]: v for (k, v) in six.iteritems(x)}
      )
  
      return docs
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate
  from turicreate import SArray
  from turicreate import SFrame
  from turicreate.toolkits._internal_utils import _raise_error_if_not_sarray
  import random
  import six
  import turicreate.toolkits._feature_engineering
label_desc: Use image node_id 8 for calling a global function with example usage: parse_docword(filename, vocab_filename) and returns: docs