old_contents: import graph
  from corpus.mysql.reddit import RedditMySQLCorpus
  
  import cred
  
  if __name__ == '__main__':
      corpus = RedditMySQLCorpus()
      corpus.setup(**(cred.kwargs))
  
      result = corpus.run_sql('SELECT * FROM comment_feature_read', None)
      print('Got results')
  
      values = [ float(v['ari']) for v in result ]
      graph.hist('data/ari_hist', values, 'ARI', 'Frequency',
                 'Frequency of ARI values')
  
      values = [ float(v['flesch_reading_ease']) for v in result ]
      graph.hist('data/flesch_reading_ease_hist', values, 'Flesch Reading Ease', 'Frequency',
                 'Frequency of Flesch Reading Ease values')
  
      values = [ float(v['flesch_kincaid_grade_level']) for v in result ]
      graph.hist('data/flesch_kincaid_grade_level_hist', values, 'Flesch Kincaid Grade Level', 'Frequency',
                 'Frequency of Flesch Kincaid Grade Level values')
  
      values = [ float(v['gunning_fog_index']) for v in result ]
      graph.hist('data/gunning_fog_index_hist', values, 'Gunning Fog Index', 'Frequency',
                 'Frequency of Gunning Fog Index values')
  
      values = [ float(v['smog_index']) for v in result ]
      graph.hist('data/smog_index_hist', values, 'Smog Index', 'Frequency',
                 'Frequency of Smog Index values')
  
      values = [ float(v['coleman_liau_index']) for v in result ]
      graph.hist('data/coleman_liau_index_hist', values, 'Coleman Liau Index', 'Frequency',
                 'Frequency of Coleman Liau Index values')
  
      values = [ float(v['lix']) for v in result ]
      graph.hist('data/lix_hist', values, 'LIX', 'Frequency',
                 'Frequency of LIX values')
  
      values = [ float(v['rix']) for v in result ]
      graph.hist('data/rix_hist', values, 'RIX', 'Frequency',
                 'Frequency of RIX values')
  
new_contents: import graph
  from corpus.mysql.reddit import RedditMySQLCorpus
  
  import cred
  
  if __name__ == '__main__':
      corpus = RedditMySQLCorpus()
      corpus.setup(**(cred.kwargs))
  
      indices = ['ari', 'flesch_reading_ease', 'flesch_kincaid_grade_level', 'gunning_fog_index', 'smog_index',
                 'coleman_liau_index', 'lix', 'rix']
  
      for i in indices:
          result = corpus.run_sql('SELECT COUNT(*) AS count, FLOOR(FLOOR(%s)/10.0)*10 AS bin '
                                       'FROM comment_feature_read '
                                       'GROUP BY bin ORDER BY bin' % i, None)
  
          values = [ (r[i], r['count']) for r in result ]
          graph.hist_prebin('data/%s_hist' % i, values, i, 'Frequency',
                            'Frequency of %s values' % i)
  
      result = corpus.run_sql('SELECT * FROM comment_feature_read', None)
  
      seen = []
      limits = {
          'ari': (-20, 100),
          'flesch_reading_ease': (-150, 200),
          'flesch_kincaid_grade_level': (-20, 50),
          'gunning_fog_index': (0, 40),
          'smog_index': (0, 20),
          'coleman_liau_index': (-30, 30),
          'lix': (0, 100),
          'rix': (0, 10)
      }
      for i in indices:
          for j in indices:
              if i == j:
                  continue
              key = tuple(sorted([i, j]))
              if key in seen:
                  continue
              seen.append(key)
              x = [ float(v[i]) for v in result ]
              y = [ float(v[j]) for v in result ]
              graph.scatter('data/%s-%s' % (i, j), x, y, limits[i], limits[j], i, j)
subject: Update histogram/scatterplot capability