<｜begin▁of▁sentence｜>### Instruction:
As a policy researcher working for a nonprofit organization focusing on environmental policies, you are responsible for analyzing data related to the impact of air pollution on different demographics. Your team has collected data on air pollution levels in various cities and the corresponding health outcomes, such as respiratory illnesses, asthma rates, and hospitalization records. You need to obtain and present the dataset in JSON format to showcase the correlation between air pollution levels and health outcomes to inform public discourse and advocacy efforts.

You are required to use the Pandas library in Python to manipulate and extract the necessary data. You have access to a DataFrame that contains air pollution levels for different cities, labeled as 'attribute1' with values ['high', 'medium', 'low'], and health outcomes represented by 'attribute2' with values [15, 20, 25]. Your task is to extract and present the list of all attributes in JSON format for further analysis and reporting.
### Response:
from igraph import Graph
import json

# Create a graph with some vertex attributes
g = Graph()
g.add_vertices(3)
g.vs['attribute1'] = ['value1', 'value2', 'value3']
g.vs['attribute2'] = [10, 20, 30]

# Obtain the list of all vertex attributes
vertex_attributes = g.vs.attributes()

# Print the list of attributes
print('Vertex Attributes:', vertex_attributes)

# Convert to JSON and print
vertex_attributes_json = json.dumps({'Vertex Attributes': vertex_attributes})
print(vertex_attributes_json)
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