<｜begin▁of▁sentence｜>### Instruction:
Imagine you're at the helm of a nonprofit organization that focuses on building community networks. Your team has been mapping out various relationships and collaborations between different local entities, and this data has been collected in a DOT format file named 'example.dot'. This file serves as a blueprint, illustrating the intricate web of connections your organization wishes to understand and utilize for strategic planning.

As the lead administrator, you need to transform this blueprint into a more manageable form. The task at hand is to import the data from the 'example.dot' file to create a more versatile representation of these connections using NetworkX, which will allow for easier analysis and manipulation. 

Specifically, the data should first be represented as a MultiGraph to ensure all the nuances of the connections are preserved. However, for the sake of simplicity and to streamline the visualization of these relationships, you will need to convert this initial MultiGraph into a straightforward Graph. In doing so, redundant connections would be merged to provide a clearer overview of the existing networks.

Once this process is completed, you decide to present the results to your board. To do so effectively, you intend to outline the nodes (representing the local entities) and the edges (symbolizing the relationships between these entities) of the resultant Graph. This visual representation is crucial in illustrating to the board how your team plans to harness these connections to advance the mission of your nonprofit.
### Response:
import networkx as nx

# Assume you have a dot file 'example.dot' with a graph defined in it
path_to_dot_file = 'example.dot'

# Read the dot file and return a MultiGraph
multi_graph = nx.nx_pydot.read_dot(path_to_dot_file)

# If you want a simple Graph instead of a MultiGraph
graph = nx.Graph(multi_graph)

# Print nodes and edges of the graph
print('Nodes:', graph.nodes())
print('Edges:', graph.edges())
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