docs: def top_corr(self, df):
          """Give aggregation counts and correlations"""
          tag_freq = df.sum()
          tag_freq.sort(ascending=False)
  
          corr = df.corr().fillna(1)
          corr_dict = corr.to_dict()
          for tag, count in tag_freq.iteritems():
              print '  %s%s: %s%s%s  (' % (color.Green, tag, color.LightBlue, count, color.Normal),
              tag_corrs = sorted(corr_dict[tag].iteritems(), key=operator.itemgetter(1), reverse=True)
              for corr_tag, value in tag_corrs[:5]:
                  if corr_tag != tag and (value > .2):
                      print '%s%s:%s%.1f' % (color.Green, corr_tag, color.LightBlue, value),
              print '%s)' % color.Normal