Node size dependent on the node degree on NetworkX

@miles82 provided a great answer. However, if you've already added the nodes to your graph using something like G.add_nodes_from(nodes), then I found that d = nx.degree(G) may not return the degrees in the same order as your nodes.

Building off the previous answer, you can modify the solution slightly to ensure the degrees are in the correct order:

d = nx.degree(G)
d = [(d[node]+1) * 20 for node in G.nodes()]

Note the d[node]+1, which will be sure that nodes of degree zero are added to the chart.

Update for those using networkx 2.x

The API has changed from v1.x to v2.x. networkx.degree no longer returns a dict but a DegreeView Object as per the documentation.

There is a guide for migrating from 1.x to 2.x here.

In this case it basically boils down to using dict(g.degree) instead of d = nx.degree(g).

The updated code looks like this:

import networkx as nx
import matplotlib.pyplot as plt

g = nx.Graph()
g.add_edges_from([(1,2), (2,3), (2,4), (3,4)])

d = dict(g.degree)

nx.draw(g, nodelist=d.keys(), node_size=[v * 100 for v in d.values()])
plt.show()

---

nx.degree(p) returns a dict while the node_size keywod argument needs a scalar or an array of sizes. You can use the dict nx.degree returns like this:

import networkx as nx
import matplotlib.pyplot as plt

g = nx.Graph()
g.add_edges_from([(1,2), (2,3), (2,4), (3,4)])

d = nx.degree(g)

nx.draw(g, nodelist=d.keys(), node_size=[v * 100 for v in d.values()])
plt.show()