Node size dependent on the node degree on NetworkX

Question

I imported my Facebook data onto my computer in the form of a .json file. The data is in the format:

{"nodes":[{"name":"Alan"},{"name":"Bob"}],"links":[{"source":0,"target:1"}]}

Then, I use this function:

def parse_graph(filename):
"""
Returns networkx graph object of facebook
social network in json format
"""
G = nx.Graph()
json_data=open(filename)
data = json.load(json_data)
# The nodes represent the names of the respective people
# See networkx documentation for information on add_* functions
G.add_nodes_from([n['name'] for n in data['nodes']])
G.add_edges_from([(data['nodes'][e['source']]['name'],data['nodes'][e['target']]['name']) for e in data['links']])
json_data.close()
return G

to enable this .json file to be used a graph on NetworkX. If I find the degree of the nodes, the only method I know how to use is:

degree = nx.degree(p)

Where p is the graph of all my friends. Now, I want to plot the graph such that the size of the node is the same as the degree of that node. How do I do this?

Using:

nx.draw(G,node_size=degree)

didn't work and I can't think of another method.

Answer 1

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()