code: def _read_dataframe(filename):
      
      # delay importing this to avoid another dependency
      import pandas
  
      # read in triples of user/artist/playcount from the input dataset
      # get a model based off the input params
      start = time.time()
      log.debug("reading data from %s", filename)
      data = pandas.read_table(filename, usecols=[0, 1, 3], names=['user', 'item', 'rating'])
  
      # map each artist and user to a unique numeric value
      data['user'] = data['user'].astype("category")
      data['item'] = data['item'].astype("category")
  
      # store as a CSR matrix
      log.debug("read data file in %s", time.time() - start)
      return data
docs: Reads the original dataset TSV as a pandas dataframe