<｜begin▁of▁sentence｜>### Instruction:
In an effort to improve the visualization of our business network relationships, we are working with a data set that represents key partnerships and interactions within our industry. The data set includes connections, specifically represented as pairs (1, 2), (1, 3), (2, 3), (2, 4), which correspond to interactions between various entities or departments within the corporate structure.

We plan to depict this network graphically to aid in our analysis and decision-making processes. To do this, we wish to employ the use of NetworkX to construct a diagram where these entities are positioned in an orderly circular formation, which would symbolize the cyclical nature of our business operations and the interconnected nature of each entity.

In addition to the fundamental structure, we find value in assigning unique identifiers or labels to each connection or edge within the network. These labels should convey specific information regarding the nature or strength of each partnership. Moreover, to enhance the visibility and interpretability of our graphical analysis, we desire that these edge labels are displayed in the color red, asserting prominence and aiding in differentiation from other elements of the graph.

Can you transform this network data into a visually impactful and informative graph that adheres to our specifications? The inclusion of custom edge labels and stylistic choices such as font color is essential to enable effective communication to stakeholders during the presentation of the analysis.
### Response:
import matplotlib.pyplot as plt
import networkx as nx

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

# Specify the positions for each node
pos = nx.circular_layout(G)

# Create edge labels
custom_edge_labels = {(1, 2): 'Edge A-B', (1, 3): 'Edge A-C', (2, 3): 'Edge B-C', (2, 4): 'Edge B-D'}

# Draw the graph
nx.draw(G, pos, with_labels=True, node_color='skyblue')

# Draw edge labels
edge_labels = nx.draw_networkx_edge_labels(G, pos, edge_labels=custom_edge_labels, font_color='red')

# Display the plot
plt.show()
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