old_contents: import pkgutil
  from io import StringIO
  
  import pandas as pd
  from scipy.stats import rankdata
  
  
  class BackgroundFrequencies(object):
  	@staticmethod
  	def get_background_frequency_df(frequency_path=None):
  		raise Exception
  
  	@classmethod
  	def get_background_rank_df(cls, frequency_path=None):
  		df = cls.get_background_frequency_df(frequency_path)
  		df['rank'] = rankdata(df.background, method='dense')
  		df['background'] = df['rank'] / df['rank'].max()
  		return df[['background']]
  
  
  class DefaultBackgroundFrequencies(BackgroundFrequencies):
  	@staticmethod
  	def get_background_frequency_df(frequency_path=None):
  		if frequency_path:
  			unigram_freq_table_buf = open(frequency_path)
  		else:
  			unigram_freq_table_buf = StringIO(pkgutil.get_data('scattertext', 'data/count_1w.txt')
  			                                  .decode('utf-8'))
  		to_ret = (pd.read_table(unigram_freq_table_buf,
  		                        names=['word', 'background'])
  		          .sort_values(ascending=False, by='background')
  		          .drop_duplicates(['word'])
  		          .set_index('word'))
  		return to_ret
  
new_contents: import pkgutil
  from io import StringIO
  
  import pandas as pd
  from scipy.stats import rankdata
  
  
  class BackgroundFrequencies(object):
      @staticmethod
      def get_background_frequency_df(frequency_path=None):
          raise Exception
  
      @classmethod
      def get_background_rank_df(cls, frequency_path=None):
          df = cls.get_background_frequency_df(frequency_path)
          df['rank'] = rankdata(df.background, method='dense')
          df['background'] = df['rank'] / df['rank'].max()
          return df[['background']]
  
  
  class DefaultBackgroundFrequencies(BackgroundFrequencies):
      @staticmethod
      def get_background_frequency_df(frequency_path=None):
          if frequency_path:
              unigram_freq_table_buf = open(frequency_path)
          else:
              unigram_freq_table_buf = StringIO(pkgutil.get_data('scattertext', 'data/count_1w.txt')
                                                .decode('utf-8'))
          to_ret = (pd.read_csv(unigram_freq_table_buf,
                                sep='\t',
                                names=['word', 'background'])
                    .sort_values(ascending=False, by='background')
                    .drop_duplicates(['word'])
                    .set_index('word'))
          return to_ret
  
subject: Fix FutureWarning: read_table is deprecated, use read_csv instead, passing sep='\t'