code: def degree(self, kind='out', weighted=True):
      '''Returns an array of vertex degrees.
      kind : either 'in' or 'out', useful for directed graphs
      weighted : controls whether to count edges or sum their weights
      '''
      if kind == 'out':
        axis = 1
        adj = self.matrix('dense', 'csc')
      else:
        axis = 0
        adj = self.matrix('dense', 'csr')
  
      if not weighted and self.is_weighted():
        # With recent numpy and a dense matrix, could do:
        # d = np.count_nonzero(adj, axis=axis)
        d = (adj!=0).sum(axis=axis)
      else:
        d = adj.sum(axis=axis)
      return np.asarray(d).ravel(f degree(self, kind='out', weighted=True):
      '''Returns an array of vertex degrees.
      kind : either 'in' or 'out', useful for directed graphs
      weighted : controls whether to count edges or sum their weights
      '''
      if kind == 'out':
        axis = 1
        adj = self.matrix('dense', 'csc')
      else:
        axis = 0
        adj = self.matrix('dense', 'csr')
  
      if not weighted and self.is_weighted():
        # With recent numpy and a dense matrix, could do:
        # d = np.count_nonzero(adj, axis=axis)
        d = (adj!=0).sum(axis=axis)
      else:
        d = adj.sum(axis=axis)
      return np.asarray(d).ravel()
docs: Returns an array of vertex degrees.
      kind : either 'in' or 'out', useful for directed graphs
      weighted : controls whether to count edges or sum their weights