Polynomial curve fitting in Python

import numpy as np
# Solutions to a system of polynomial coefficients Xa = f

# the x-coordinates of the points we know
x = np.array([0, 1, 2, 3, 4, 5, 6, 6.7, 7.5])

# plugs x into f(x) = Σa_i*x^i and represents it as a vector for each value of x, creating a matrix
# when multiplied by the appropriate coefficient vector a, we get a vector of f(x)
to_poly = lambda x : np.array([x ** (i) for i in range(len(x))]).T
X = to_poly(x)

# the f(x) values corresponding to the x-coordinates
f = np.array([0, 1.1, 1.5, 1.6, 1.55, 1.4, 1, 0.5, 0])

# solves the system
a = (np.linalg.solve(X, f))

# formatting mumbo-jumbo; the '10' specifies 10 decimal places
print('[%s]' % ', '.join(map(str, ['%.10f' % r for r in a])))

# creates the polynomial in Python (numpy)
p = np.poly1d(a[::-1])

# check if (x, f(x)) is correct
for r in x:
    print('p(', r, ')', '=', p(r), end= ', ', sep='')