<｜begin▁of▁sentence｜>### Instruction:
Imagine you're stationed in a remote village, and the community has asked for your assistance in mapping out their new communication network to enhance local development. They've decided to adopt a novel approach: each household will be a node in the network, and a direct line of communication can only be established between households that are less than 0.2 units of distance apart. There are 100 households in the village, and they're curious about how this communication network might look.

To help them visualize their plan, you've thought of creating a model using NetworkX to simulate this network of households. You want to form a random geometric graph that represents their community, where every node exemplifies a household, and edges connect nodes that are no further than 0.2 units apart, based on the Euclidean distance between them. This will give the villagers a clear picture of how their communication network could be structured, accounting for proximity as the key factor. How would you go about visualizing such a graph to effectively communicate your findings to the village committee?
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Create a random geometric graph with 100 nodes
# where nodes are joined by an edge
# if their Euclidean distance is at most 0.2
G = nx.random_geometric_graph(100, 0.2)

# Draw the graph
nx.draw(G, nx.get_node_attributes(G, 'pos'), node_size=50, node_color='blue', with_labels=False)
plt.show()
<|EOT|>
