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import numpy as np
from scipy import optimize

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def func(x, a, b, c):
return a * np.exp(-b * x) + c

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params, params_covariance = optimize.curve_fit(func, x_data, y_data)

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x_fit = np.linspace(min(x_data), max(x_data), 100)
y_fit = func(x_fit, params[0], params[1], params[2])
import matplotlib.pyplot as plt
plt.scatter(x_data, y_data, label='Data')
plt.plot(x_fit, y_fit, label='Fit')
plt.legend()
plt.show()

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