<｜begin▁of▁sentence｜>### Instruction:
As a survey researcher tasked with analyzing data on social network connections within a large organization, you have obtained a dataset representing a bipartite network with 50 employees on one side and 50 projects on the other. Each edge represents a collaboration opportunity, with a 25% probability of connection between employees and projects.

To extract insights from this network, you are exploring the use of the condor function in cdlib, a tool commonly used in social network analysis. How can you leverage this function to perform community detection and identify meaningful clusters within this bipartite network of employee-project collaborations?
### Response:
import networkx as nx
from cdlib import algorithms

# Create a bipartite graph
G = nx.algorithms.bipartite.random_graph(50, 50, 0.25)

# Apply the CONDOR algorithm for bipartite community detection
coms = algorithms.condor(G)
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