docs: def get_std_xy_dataset_statistics(x_values, y_values, expect_negative_correlation = False, STDev_cutoff = 1.0):
      '''Calls parse_csv and returns the analysis in a format similar to get_xy_dataset_statistics in klab.stats.misc.'''
      assert(len(x_values) == len(y_values))
      csv_lines = ['ID,X,Y'] + [','.join(map(str, [c + 1, x_values[c], y_values[c]])) for c in xrange(len(x_values))]
      data = parse_csv(csv_lines, expect_negative_correlation = expect_negative_correlation, STDev_cutoff = STDev_cutoff)
  
      assert(len(data['predictions']) == 1)
      assert(1 in data['predictions'])
      assert(data['predictions'][1]['name'] == 'Y')
      summary_data = data['predictions'][1]
  
      stats = {}
      for spair in field_name_mapper:
          stats[spair[1]] = summary_data[spair[0]]
      if stats['std_warnings']:
          stats['std_warnings'] = '\n'.join(stats['std_warnings'])
      else:
          stats['std_warnings'] = None
      return stats