Question

In: Computer Science

PYTHON First, create an ER random graph with N=100 and p=0.1 and name it G. Then...

PYTHON

First, create an ER random graph with N=100 and p=0.1 and name it G. Then use the histogram() function to draw a histogram of the node degrees for the graph G. Don't worry about filling in "missing" values.

Also print the mean, median, and mode of the node degree distribution. Execute this a few times.

Note: while histogram(G.degree()) does draw a plot, that plot is not a histogram. Doing so will result in zero credit for this exercise.

Expert Solution

import networkx as nx

import matplotlib.pyplot as plt

import numpy as np

import statistics

G= nx.erdos_renyi_graph(100,0.1)

nodes = nx.nodes(G)

degrees = []

for v in nodes:

degrees.append(nx.degree(G, v))

plt.hist(degrees,color = 'green')

plt.show()

print("Mean: ",np.mean(degrees))

print("Median: ",np.median(degrees))

print("Mode: ",statistics.mode(degrees))

venereology answered 11 months ago

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