<｜begin▁of▁sentence｜>### Instruction:
As a science journalist reporting on network analysis tools for a tech magazine, let's delve into a practical scenario. Imagine you're a data scientist tasked with analyzing a complex network of connections between different nodes. You have a graph represented by a set of edges: [(0, 1), (1, 2), (2, 3), (3, 0), (0, 2)]. Your goal is to uncover a foundational cycle basis of this graph to better understand its structural characteristics.

To accomplish this, you're interested in utilizing the 'fundamental_cycles' function from the igraph API, a powerful tool widely used in network analysis. This function is designed to extract fundamental cycles from a given graph, providing insights into its underlying cyclic structures. By applying this function, you aim to identify a comprehensive set of fundamental cycles that form the basis of the network's connectivity.

In essence, your task is to leverage igraph's functionality to derive a single fundamental cycle basis for the provided graph, enabling you to gain deeper insights into its topological properties and relational dynamics.
### Response:
import igraph as ig

# Create a graph with edges
g = ig.Graph(edges=[(0, 1), (1, 2), (2, 3), (3, 0), (0, 2)])

# Get the fundamental cycle basis of the graph
fundamental_cycles = g.fundamental_cycles()

# Print out the fundamental cycles
print(fundamental_cycles)
<|EOT|>
