Degree centrality over time
Now, you're going to plot the degree centrality distribution over time. Remember that the ECDF function will be provided, so you won't have to implement it.
Questo esercizio fa parte del corso
Intermediate Network Analysis in Python
Istruzioni dell'esercizio
- Create a list of degree centrality scores month-by-month. To do this:
- In each iteration of the first
forloop, compute the degree centrality ofGusing thenx.degree_centrality()function. Save the result ascent. - Append
centto the listcents.
- In each iteration of the first
- Plot ECDFs over time. To do this:
- Iterate over
range(len(cents))using aforloop. Inside the loop, use theECDF()function withcents[i].values()as the argument. Unpack the output of this intoxandy. - Pass
xandyas arguments toplt.plot().
- Iterate over
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Import necessary modules
import networkx as nx
import matplotlib.pyplot as plt
# Create a list of degree centrality scores month-by-month
cents = []
for G in Gs:
cent = ____
____
# Plot ECDFs over time
fig = plt.figure()
for i in ____:
____, ____ = ____
plt.plot(____, ____, label='Month {0}'.format(i+1))
plt.legend()
plt.show()