from_dict_of_dicts(d, create_using=None, multigraph_input=False)

Parameters

d : dictionary of dictionaries

A dictionary of dictionaries adjacency representation.

create_using : NetworkX graph constructor, optional (default=nx.Graph)

Graph type to create. If graph instance, then cleared before populated.

multigraph_input : bool (default False)

When True, the dict d is assumed to be a dict-of-dict-of-dict-of-dict structure keyed by node to neighbor to edge keys to edge data for multi-edges. Otherwise this routine assumes dict-of-dict-of-dict keyed by node to neighbor to edge data.

Returns a graph from a dictionary of dictionaries.

Examples

>>> dod = {0: {1: {"weight": 1}}}  # single edge (0,1)
... G = nx.from_dict_of_dicts(dod)

or

>>> G = nx.Graph(dod)  # use Graph constructor

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.convert.from_dict_of_dicts networkx.convert.to_dict_of_dicts

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

GitHub : /networkx/convert.py#364
type: <class 'function'>
Commit: