Matplotlib and NetworkX are two powerful Python libraries that can be used to create visualizations of network data. Matplotlib is a data visualization library that can be used to create a wide range of charts, plots, and graphs, while NetworkX is a library for working with and visualizing graphs and networks.

Here’s a basic example of using these libraries to create a simple network visualization:

import networkx as nx
import matplotlib.pyplot as plt

# Create a new graph
G = nx.Graph()

# Add nodes to the graph
G.add_node(1)
G.add_node(2)
G.add_node(3)
G.add_node(4)

# Add edges to the graph
G.add_edge(1, 2)
G.add_edge(1, 3)
G.add_edge(1, 4)

# Draw the graph using Matplotlib
nx.draw(G, with_labels=True)
plt.show()

In this example, we first import the NetworkX and Matplotlib libraries. We then create a new graph object using the Graph class from NetworkX, and add four nodes and three edges to the graph. Finally, we use the draw function from NetworkX to draw the graph using Matplotlib, and display it using the show function.

This is just a basic example, but with these libraries you can create much more complex and detailed visualizations of network data. For example, you can use NetworkX to load network data from various sources (such as CSV files or online data sources) and perform various graph algorithms on the data, such as calculating shortest paths or clustering coefficients. You can then use Matplotlib to create visualizations of the resulting graph data in a variety of formats, such as bar charts, scatter plots, or network diagrams.

Overall, using these libraries together can be a powerful way to analyze and visualize network data in a clear and intuitive way.