<｜begin▁of▁sentence｜>### Instruction:
Step right up, step right up! Imagine we're under the big top, and in our act today, we've got a magnificent display of interconnected trapeze artists swinging to and fro, each representing a point on a grand network of performers. Now, as in any good spectacle, we have a few soloists, those artists who occasionally swing back to their own platforms - ah, yes, these daredevils are akin to those self-loops in a NetworkX graph that we're so curious about.

Now, picture this: we want a seamless performance, each artist swinging to another's platform, no repeat performances on their own. So here's the act I have in mind: we want to employ the spellbinding 'remove_loops' function from the 'graspologic.utils' troupe to whisk away all those solo moments and ensure that every single swing is towards another performer.

The question is, can this fantastic 'remove_loops' trick clean up our act, so to speak, and remove every self-loop from our network, leaving us with a flawless routine where no performer swings back to their own platform? What say you, can the magic of 'graspologic.utils' transform our intricate performance into one without any self-encounters?
### Response:
import networkx as nx
from graspologic.utils import remove_loops

# Create a NetworkX graph with self-loops
G = nx.Graph()
G.add_edge(1, 1)
G.add_edge(1, 2)
G.add_edge(2, 2)

# Remove self-loops from the graph
G_clean = remove_loops(G)

# Verify that the self-loops are removed
print(nx.selfloop_edges(G_clean))
<|EOT|>
