Make Networkx Plot Look Nice

I would need to build a nice network using the following data: result_set = {('name1', 'job1'), ('name2', 'job2'), ('name3', 'job3'), ('name4', 'job4'), ('name5', 'job5'), ('name6'

Solution 1:

You can use one of the many layout algorithms implemented in networkx in nx.drawing.layout to position the nodes in a way that makes the visualisation of the network easier. You can further adjust the distance between the nodes by setting k to an appropriate value.

Also you can set the node size to be proportional to the degree by building a dict from Graph.degree and setting the node_size in nx.draw accordingly and scaling it up to the desired size by applying a multiplicative factor. Here's an example using spring_layout:

from pylab import rcParams
rcParams['figure.figsize'] = 14, 10
pos = nx.spring_layout(G, scale=20, k=3/np.sqrt(G.order()))
d = dict(G.degree)
nx.draw(G, pos, node_color='lightblue', 
        with_labels=True, 
        nodelist=d, 
        node_size=[d[k]*300for k in d])

You could also custom the node colour according to whether a node is a job or a name using the node_color parameter (I'm guessing this is not the real case but it gives an idea of how to proceed):

rcParams['figure.figsize'] = 14, 10pos = nx.spring_layout(G, scale=20, k=3/np.sqrt(G.order()))
colors = [['lightgrey', 'lightblue'][node.startswith('job')] 
          for node in G.nodes()]
d = dict(G.degree)
nx.draw(G, pos, 
        with_labels=True, 
        nodelist=d, 
        node_size=[d[k]*300for k in d],
        node_color=colors)