<｜begin▁of▁sentence｜>### Instruction:
As a Project Coordinator for our network infrastructure project, I would like your assistance with a task that is critical for our planning stage. We are currently examining two different types of network topologies that we might implement across our offices. The first topology is a linear chain structure which connects five departments in a series (this can be visualized as a path graph with 5 nodes). The second topology under consideration is a bit more complex, featuring two separate pairs of departments that are interconnected, but these pairs are not connected to each other (imagine a disconnected graph with two components, each component being a pair of connected nodes).

To proceed with our assessment, we need to understand the communication efficiency within these proposed network structures. As such, could you compute the average shortest path length for the linear chain structure, as well as for each individual pair in the segmented topology? This will give us crucial insight into the potential speed of communication flow within each proposed network setup. 

Keep in mind there are no external data files, like a GML, involved in this scenario – just the conceptual data provided. Your calculations will help us move forward in determining which network topology might best suit our project's needs.
### Response:
import networkx as nx

# Create a path graph of 5 nodes
G = nx.path_graph(5)

# Compute the average shortest path length
average_path_length = nx.average_shortest_path_length(G)
print('Average shortest path length:', average_path_length)

# For handling disconnected graphs, one can compute average
# shortest path length for each component separately
H = nx.Graph([(1, 2), (3, 4)])
for C in nx.connected_components(H):
    subgraph = H.subgraph(C).copy()
    component_average_path_length = nx.average_shortest_path_length(subgraph)
    print('Component average shortest path length:', component_average_path_length)
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