<｜begin▁of▁sentence｜>### Instruction:
Given a dataset representing the distribution of fractures in a specific population, let's say a series of patients seen in an orthopedic practice over a period of time, with the frequency of fractures following a pattern similar to the sequence [i**-2.5 for i in range(1, 1000)], could you analyze this data using the PowerLawFit API in NetworkX? Once fitted, you're required to utilize the __str__ method of the fitted object to retrieve a string representation containing essential information about how well the power-law distribution fits the data.
### Response:
from powerlaw import Fit
import matplotlib.pyplot as plt

# Generate synthetic data with a power-law distribution
synthetic_data = [i**-2.5 for i in range(1, 1000)]

# Fit the data to a power-law distribution
fit = Fit(synthetic_data)

# Obtain the __str__ representation of the fitted power law
str_representation = fit.power_law.__str__()
print(str_representation)
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