<｜begin▁of▁sentence｜>### Instruction:
Picture this: you're starring in the latest animated feature about a bustling Karate Club, a community of characters connected by their interactions, much like friends in a town or heroes in an adventure. The interactions are so crucial that they've become visual; think of it like a mystical map, spelling out the bonds between our heroes.

As the voice behind the wise Network Sage, you're explaining to the young protagonist that each member of the club, every character they meet, is represented by a node on this enchanted map. The lines between them, the edges, symbolize their camaraderie and collaborations.

Now, here's where the magic of color comes in. In your sage voice, you describe how we can make this map even more informative. The idea is to use shades of color that deepen with the strength of each connection—so the more a character interacts, the richer their hue.

The spell we're casting to achieve this is known as `sequential_colors` from the mystical library of graspyologic. By invoking this incantation, we'll conjure up a color scheme directly tied to the number of connections each member has—their degree in network-speak—so the map not only informs but enthralls.

How would you, as the Network Sage, weave this narrative into the story, ensuring the young hero understands that their journey will be enlightened by this colorful display of connectivity? How would the colors shift and change as the ties within the club grow and evolve?
### Response:
import graspologic.layouts as glt
import matplotlib.pyplot as plt
import networkx as nx

# Create a graph
G = nx.karate_club_graph()

# Let's assign a value to each node based on its degree
degree_dict = {node: val for node, val in G.degree()}

# Generate a node color mapping using sequential colors
node_colors = glt.sequential_colors(degree_dict, light_background=True, use_log_scale=False)

# Draw the graph
nx.draw(G, node_color=list(node_colors.values()), with_labels=True)
plt.show()
<|EOT|>
