old_contents: """Load movie summaries and genres from file.
  """
  
  import pandas as pd
  
  from . import utils
  
  DEFAULT_DATA_PATH = 'movie_data.csv'
  
  
  def filter_genres_summaries(data):
      """Given a DataFrame of movie genres and summaries, filter rows according
      to the minimum lengths of the genre and summary strings.
      """
      return data[
          (data['genres'].str.len() > 2) &
          (data['summary'].str.len() > 0)]
  
  
  def load_summaries_genres(path=None):
      """Load movie summaries and genres as separate arrays.  The rows are
      filtered to remove entries with empty genre lists and , but the genres and
      summaries are unprocessed.
      """
  
      if path is None:
          path = utils.local_filepath(DEFAULT_DATA_PATH)
  
      drop_cols = [
          'id', 'title', 'release_date',
          'runtime', 'box_office_revenue']
      df = filter_genres_summaries(
          pd.read_csv(path)
          .drop(drop_cols, axis=1))
      return (df['summary'].values, df['genres'].values)
  
new_contents: """Load movie summaries and genres from file.
  """
  
  import pandas as pd
  
  
  def filter_genres_summaries(data):
      """Given a DataFrame of movie genres and summaries, filter rows according
      to the minimum lengths of the genre and summary strings.
      """
      return data[
          (data['genres'].str.len() > 2) &
          (data['summary'].str.len() > 0)]
  
  
  def load_summaries_genres(path):
      """Load movie summaries and genres as separate arrays.  The rows are
      filtered to remove entries with empty genre lists and , but the genres and
      summaries are unprocessed.
      """
  
      drop_cols = [
          'id', 'title', 'release_date',
          'runtime', 'box_office_revenue']
      df = filter_genres_summaries(
          pd.read_csv(path)
          .drop(drop_cols, axis=1))
      return (df['summary'].values, df['genres'].values)
  
subject: move some things around