<｜begin▁of▁sentence｜>### Instruction:
As a business analyst tasked with evaluating the mutual collaboration within our corporate network, we're interested in understanding the extent of bidirectional partnerships versus unidirectional outreach occurring among different departments. Our current network data - let's call it 'CorporatePartnerships.gml' - includes instances of two-way interactions, such as between the Sales (A) and Marketing (B) departments, as well as Marketing (B) and Logistics (C). We also have recorded cases of one-way communication, where Logistics (C) reaches out to Production (D), which in turn communicates with Quality Assurance (E), without a reciprocated response.

In order to quantify the degree of this reciprocity and gain insights into mutual exchanges across the network, could you demonstrate how to compute the overall reciprocity rate of these interactions using the NetworkX tool? This figure will help us target areas for improvement in our inter-departmental collaboration strategies.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add edges (some edges are added in both directions to create reciprocity)
G.add_edge('A', 'B')
G.add_edge('B', 'A') # Reciprocal of A -> B
G.add_edge('B', 'C')
G.add_edge('C', 'B') # Reciprocal of B -> C
G.add_edge('C', 'D')
G.add_edge('D', 'E')

# Compute the overall reciprocity of the graph
reciprocity = nx.overall_reciprocity(G)

print('Overall reciprocity of the graph:', reciprocity)
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