<｜begin▁of▁sentence｜>### Instruction:
Imagine you're a work-from-home freelancer tasked with an intriguing project by an innovative networking startup. They are exploring novel ways to visualize and understand complex networks, particularly those that naturally emerge in social media, academic citations, or internet infrastructure. Your mission, should you choose to accept it, involves leveraging your creativity and technical skills to shed light on these networks.

Here's the deal: The startup is interested in networks where connections aren't just random but follow a specific pattern known as a power law distribution. This pattern is everywhere - from the way people interact on social media to how citations are distributed among academic papers. It's a fingerprint of collective behavior and structure.

**Project Brief:**

**Objective:** Create a captivating visual representation of a network. But not just any network. This one has to mirror the intricacies of real-world networks by having its nodes connected in a way that follows a power law distribution. 

**Specifications:**

- **Length n (Number of Nodes):** 10 - Representing the number of elements within your network.
- **Exponent (Power Law Distribution):** 2.5 - This parameter will guide how the connections between the nodes are distributed. It's a crucial piece of the puzzle that ensures your network closely resembles those found in nature and human-made systems.

**Your mission:** Tap into the powerlaw_sequence function from NetworkX, a powerful Python library, to generate a degree sequence that adheres to the specified power law distribution. With this sequence, construct and visualize a random graph. This visual representation is not just a deliverable for your client; it's a window into understanding how complex systems organically organize and scale.

Think of this as creating a miniature universe governed by the laws of connectivity and distribution. Your finished graph will serve as both a technical achievement and a piece of digital art, showcasing how even seemingly random connections have an underlying order dictated by the power law.

Once completed, your visualization will be a key piece in the startup's exploration into the fabric of complex networks, potentially guiding future innovations or revealing new insights into the nature of connectivity.

Let your creativity and technical expertise shine through this project, and may it be a fulfilling addition to your portfolio as a forward-thinking freelancer. Good luck!
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Generate a power law sequence of length n
sequence = nx.utils.powerlaw_sequence(10, exponent=2.5)

# Create a graph with degree drawn from the power law sequence
G = nx.expected_degree_graph(sequence, selfloops=False)

# Drawing the graph
nx.draw(G, with_labels=True)
plt.show()
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