Degree centrality distribution of project nodes
Now it's time to plot the degree centrality distribution for the 'projects'
partition of G
. The steps to do this are exactly the same as in the previous exercise. For your convenience, matplotlib.pyplot
has been pre-imported as plt
.
Go for it!
This exercise is part of the course
Intermediate Network Analysis in Python
Exercise instructions
- Obtain a list called
project_nodes
corresponding to the'projects'
nodes ofG
. - Using the
nx.degree_centrality()
function, compute the degree centralities for each node inG
. Store the result asdcs
. - Use a list comprehension to compute the degree centralities for each node in
project_nodes
. Store the result asproject_dcs
. - Plot a histogram of the degree distribution of projects, using
plt.hist()
andproject_dcs
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Get the 'projects' nodes: project_nodes
project_nodes = ____
# Compute the degree centralities: dcs
dcs = ____
# Get the degree centralities for project_nodes: project_dcs
project_dcs = [____]
# Plot the degree distribution of project_dcs
plt.yscale('log')
plt.hist(____, bins=20)
plt.show()