<｜begin▁of▁sentence｜>### Instruction:
As an expert in network analysis using `networkx`, let me assist you in a practical scenario. Suppose you are working on analyzing a social network of 10 individuals where the likelihood of a connection between any two individuals is 50%. You are interested in calculating the eccentricity of each individual, which represents the maximum distance between that individual and any other individual in the network. 

Now, if you were using the `eccentricity` function in the `networkx` library, you could effectively determine and display the eccentricities of all individuals within the network.
### Response:
from igraph import Graph

# Create a graph
g = Graph.Erdos_Renyi(n=10, p=0.5)

# Calculate the eccentricities of all vertices
eccentricities = g.eccentricity(vertices=None, mode='all', weights=None)

# Print the eccentricities
for vertex, ecc in enumerate(eccentricities):
    print(f'Vertex {vertex}: Eccentricity = {ecc}')
<|EOT|>
