<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on a public health initiative focused on developing a sophisticated communication network. This network aims to model how information on wellness and disease prevention spreads throughout a community. For this task, you've chosen to use a specialized type of graph that exemplifies complex connectivity—namely, the Mycielski Graph.

Your objective is to create an educational tool that visualizes the connectivity of this network. To do so, you will need to construct and examine the 4th iteration of the Mycielski Graph, which is known for its unique properties of being triangle-free and chromatic.

Could you explore how to utilize NetworkX's 'mycielski_graph' function to bring forth the 4th Mycielski Graph? Upon its creation, we would like to analyze its attributes, including the number of nodes, edges, and other relevant information that might illuminate our understanding of its structure. Your insights will be instrumental in fine-tuning our communication strategies within the community health education programs.
### Response:
import networkx as nx

# Generate the n-th Mycielski Graph
n = 4
G = nx.generators.small.mycielski_graph(n)

# Print information about the graph
print(nx.info(G))
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