code: def nqueen_graph(self):
          
          # Filters out boards with pieces other than queens.
          nqueens = self.results
          for piece_label in set(PIECE_LABELS).difference(['queen']):
              nqueens = nqueens[nqueens[piece_label].map(pandas.isnull)]
  
          # Filters out non-square boards whose dimension are not aligned to the
          # number of queens.
          nqueens = nqueens[nqueens['length'] == nqueens['queen']]
          nqueens = nqueens[nqueens['height'] == nqueens['queen']]
  
          # Filters out results not obtained from this system.
          for label, value in self.context.items():
              if not value:
                  nqueens = nqueens[nqueens[label].map(pandas.isnull)]
              else:
                  nqueens = nqueens[nqueens[label] == value]
  
          plot = seaborn.factorplot(
              x='queen',
              y='execution_time',
              data=nqueens.sort(columns='queen'),
              estimator=median,
              kind='bar',
              palette='BuGn_d',
              aspect=1.5)
          plot.set_xlabels('Number of queens')
          plot.set_ylabels('Solving time in seconds (log scale)')
          plot.fig.get_axes()[0].set_yscale('log')
  
          plot.savefig('nqueens-performances.png')
docs: Graph n-queens problem for the current version and context.