<｜begin▁of▁sentence｜>### Instruction:
In our pursuit of creating a more inclusive and harmoniously connected environment within the organization's network, let's consider the metaphorical pathway that ideas travel between different teams. Imagine our network consists of various nodes representing teams or individuals: Team 1, Team 2, and so on, with connections akin to the following relationships: Team 1-Team 2, Team 1-Team 3, Team 1-Team 4, Team 3-Team 4, Team 3-Team 5, and Team 4-Team 5. 

To ensure that the flow of ideas and resources between Team 1 and Team 3 is as efficient and unimpeded as possible, symbolizing a strong inclusive link, we are interested in determining the "resistance distance"—a measure reflective of how well connected these two nodes are within the larger network.

Could you assist us in quantifying this resistance distance within our network infrastructure, utilizing NetworkX? This will enable us to understand the current state of inter-team collaboration and identify areas for improvement in our diversity and networking strategy.
### Response:
import networkx as nx

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

# Calculate resistance distance between nodes 1 and 3
resistance_dist = round(nx.resistance_distance(G, 1, 3), 10)

print('Resistance distance between node 1 and 3:', resistance_dist)
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