<｜begin▁of▁sentence｜>### Instruction:
As a Grant Coordinator, imagine you're assisting a community organization dedicated to improving transportation infrastructure. They're planning to enhance their network of roads and pathways to facilitate better connectivity between neighborhoods. To strategize effectively, they've collected data on existing routes and connections using the GraphXplorer API, which provides detailed insights into the network topology.

The organization's goal is to identify key locations where new pathways should be constructed to maximize accessibility for residents. To achieve this, they need to calculate the betweenness centrality of various vertices in their network. Specifically, they're interested in assessing the importance of vertices 0 to 5, which represent potential starting points or destinations for new pathways.

By analyzing the betweenness centrality of these vertices, the organization can prioritize areas that act as crucial hubs in the transportation network, facilitating smoother and more efficient travel for community members. With this information, they'll be better equipped to make informed decisions when applying for grants to fund the expansion and improvement of their transportation infrastructure.
### Response:
from igraph import Graph

# Create the graph
edges = [(0, 1), (0, 2), (1, 2), (2, 3), (3, 4), (4, 5), (5, 3)]
g = Graph(edges)

# Calculate betweenness
vertices_to_check = [0, 1, 2, 3, 4, 5]
betweenness_scores = g.betweenness(vertices=vertices_to_check, directed=False, cutoff=2, weights='weight', sources=None, targets=None)
print(betweenness_scores)
<|EOT|>
