<｜begin▁of▁sentence｜>### Instruction:
In your role as a professor teaching a course on network analysis at a prestigious university, you've recently come across a fascinating dataset relating to American College Football networks. You've obtained a GML file named "football.gml" that represents this network graph, showcasing the relationships between different college football teams.

Now, as part of your class project, you're tasked with demonstrating the interoperability between different network analysis libraries. You need to showcase how one can convert this network graph, as represented in NetworkX format, into the igraph format without accounting for the directionality of edges. This demonstration will not only deepen your students' understanding of network analysis but also highlight the versatility of utilizing various libraries in research and analysis.

Your goal is to integrate this technical process seamlessly into your teaching curriculum, ensuring that your students grasp the practical implications of working with different network analysis tools.
### Response:
import networkx as nx
from cdlib.utils import convert_graph_formats

# Read the American College football network
G_nx = nx.read_gml('football.gml')

# Convert NetworkX graph to igraph
G_ig = convert_graph_formats(G_nx, desired_format='igraph', directed=False)

print(type(G_ig))
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