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Diffstat (limited to 'doc/tutorial.rst')
| -rw-r--r-- | doc/tutorial.rst | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/doc/tutorial.rst b/doc/tutorial.rst index c9125eaa..fdfc9302 100644 --- a/doc/tutorial.rst +++ b/doc/tutorial.rst @@ -137,7 +137,7 @@ better in other contexts. .. nbplot:: >>> list(G.nodes) - ['a', 1, 2, 3, 'spam', 'm', 'p', 's'] + [1, 2, 3, 'spam', 's', 'p', 'a', 'm'] >>> list(G.edges) [(1, 2), (1, 3), (3, 'm')] >>> list(G.adj[1]) # or list(G.neighbors(1)) @@ -296,7 +296,7 @@ Add node attributes using ``add_node()``, ``add_nodes_from()``, or ``G.nodes`` {'time': '5pm'} >>> G.nodes[1]['room'] = 714 >>> G.nodes.data() - NodeDataView({1: {'room': 714, 'time': '5pm'}, 3: {'time': '2pm'}}) + NodeDataView({1: {'time': '5pm', 'room': 714}, 3: {'time': '2pm'}}) Note that adding a node to ``G.nodes`` does not add it to the graph, use ``G.add_node()`` to add new nodes. Similarly for edges. @@ -450,7 +450,7 @@ functions such as: >>> G.add_edges_from([(1, 2), (1, 3)]) >>> G.add_node("spam") # adds node "spam" >>> list(nx.connected_components(G)) - [set([1, 2, 3]), set(['spam'])] + [{1, 2, 3}, {'spam'}] >>> sorted(d for n, d in G.degree()) [0, 1, 1, 2] >>> nx.clustering(G) @@ -463,7 +463,7 @@ These are easily stored in a `dict` structure if you desire. >>> sp = dict(nx.all_pairs_shortest_path(G)) >>> sp[3] - {1: [3, 1], 2: [3, 1, 2], 3: [3]} + {3: [3], 1: [3, 1], 2: [3, 1, 2]} See :doc:`/reference/algorithms/index` for details on graph algorithms supported. |