<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on optimizing the layout of a farm where different crops (nodes) are connected by paths (edges) representing how they benefit from each other when planted in proximity. The edge set for the relationships among these crop plots is as follows: [(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (4, 6), (5, 6)]. You're interested in utilizing the concept of maximal cliques, where a clique is a group of crops that are all interconnected by beneficial paths, to ensure each plot receives the maximum advantage from its neighbors.

Could you utilize the 'number_of_cliques' function from NetworkX to examine our agricultural system and tell me the number of maximal beneficial groupings each crop plot is a part of? Specifically, I'm curious to know about plot number 4 – how many maximal advantageous groupings does it belong to in this farm layout?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (4, 6), (5, 6)])

# Compute the number of maximal cliques a node is part of
node_cliques = nx.number_of_cliques(G)

# For a specific node
node_4_cliques = nx.number_of_cliques(G, 4)

print("Number of maximal cliques for each node:", node_cliques)
print("Number of maximal cliques node 4 is part of:", node_4_cliques)
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