<｜begin▁of▁sentence｜>### Instruction:
In the glamorous world of fashion modeling, where the spotlight shines on the swirl of social interactions and professional engagements, a fashion model is looking to step into the role of a network analyst for their latest project. They are working with a unique fabric of connections, weaving together the individuals they've encountered on their journey - fellow models, designers, photographers - all interlinked in a dazzling social tapestry. This network, intricate and vibrant, symbolizes the professional relationships and interactions within the fashion industry, currently styled in the elegant form of a NetworkX graph.

To bring this project to the runway, the model-turned-analyst wishes to tailor this existing NetworkX graph into a more versatile and fashion-forward format, cutting and shaping it so it fits seamlessly into the graspologic framework’s wardrobe. This transformation is crucial for the graph to be accessorized with advanced analysis techniques within graspologic, ensuring that every pattern and connection in the social fabric is highlighted to perfection.

Therefore, the spotlight question shimmering on the runway is: How can the import_graph function be employed as the designer tool to refashion the NetworkX graph? This process must ensure the graph not only transitions elegantly from its original NetworkX couture into a chic, array-like ensemble that graspologic can drape, layer, and stitch with its sophisticated graph processing functionalities but also maintains its structure and essence suitable for the cutting-edge analysis in the vibrant world of fashion networking.
### Response:
import networkx as nx
from graspologic.utils import import_graph

# Create a sample NetworkX graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 4), (3, 4)])

# Use the import_graph function
g = import_graph(G, copy=True)

# g now represents the graph shared data type which can be used within graspologic
print(g)
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