<｜begin▁of▁sentence｜>### Instruction:
Imagine you're tracking a group of animals in the wilderness, each of which tends to roam with certain other animals, forming a complex web of associations. We can think of these associations as connections or pathways in your conservation area. Some of these animals are more central to this web, consistently interacting with many others, while some are more on the periphery, with fewer connections.

Now, let's say you're interested in identifying the core group of animals that are most interconnected and form the heart of this social network. To do this, we have mapped out the relationships like pathways between points (animals) as follows: (0 is connected with 1, 1 with 2, 1 with 3, 2 with 3, 2 with 4, 3 with 4, and 3 with 5).

Could you use your expertise in network analysis to pinpoint the so-called "2-core" of this network? This means we're looking for the subset of animals that have at least two other animals they frequently roam with. Identifying this 2-core group will help us focus our efforts on the animals most crucial to the social fabric of the wild population. Please list out the individual animals and their connections that form this 2-core community for us.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 3), (2, 4), (3, 4), (3, 5)])

# Compute the 2-core of G
k_core_subgraph = nx.k_core(G, k=2)

# Print the nodes in the 2-core
print('Nodes in the 2-core:', k_core_subgraph.nodes())
# Print the edges in the 2-core
print('Edges in the 2-core:', k_core_subgraph.edges())
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