<｜begin▁of▁sentence｜>### Instruction:
As a data visualization specialist using the Matplotlib integration with network analysis, you might need to visualize the degree distribution of an Erdős-Rényi graph with 100 vertices and a probability of 0.1 for edge creation. In this scenario, you are aiming to showcase the distribution of degrees within the graph to analyze the connectivity patterns. This visualization can serve as valuable insight into the structure and behavior of the network.
### Response:
from igraph import Graph, Histogram
from igraph.drawing import Plot
from igraph.drawing.matplotlib import MatplotlibHistogramDrawer
import matplotlib.pyplot as plt

# Generating some data to create a histogram
graph = Graph.Erdos_Renyi(n=100, p=0.1)
degree_sequence = graph.degree()
histogram = Histogram(bin_width=1)
histogram.update(degree_sequence)

# Create a plot object
plot = Plot()

# Add the histogram to the plot with a MatplotlibHistogramDrawer
mh_drawer = MatplotlibHistogramDrawer()
ax = plt.gca() # Get current axes
mh_drawer.draw(histogram=plt.gca(), matrix=histogram)

# Display the plot
plt.show()
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