code: def prepare(topic_model, docs, **kargs):
      """Transforms the GraphLab TopicModel and related corpus data into
      the data structures needed for the visualization.
  
      Parameters
      ----------
      topic_model : graphlab.toolkits.topic_model.topic_model.TopicModel
          An already trained GraphLab topic model.
      docs : SArray of dicts
          The corpus in bag of word form, the same docs used to train the model.
      **kwargs :
          additional keyword arguments are passed through to :func:`pyldavis.prepare`.
  
      Returns
      -------
      prepared_data : PreparedData
          the data structures used in the visualization
  
      Example
      --------
      For example usage please see this notebook:
      http://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/GraphLab.ipynb
      """
      opts = fp.merge(_extract_data(topic_model, docs), kargs)
      return pyLDAvis.prepare(**opts)
  
file_path: pyLDAvis/pyLDAvis/graphlab.py
imports: import funcy
  import numpy
  import pandas
  import graphlab
  import pyLDAvis
label_desc: Use image node_id 6 for calling a global function with example usage: prepare(topic_model, docs) and returns: pyLDAvis