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DS-1000 / 713 / I have a set of data and I want to compare which line describes it best…

Problem

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Problem:
I have a set of data and I want to compare which line describes it best (polynomials of different orders, exponential or logarithmic).
I use Python and Numpy and for polynomial fitting there is a function polyfit(). But I found no such functions for exponential and logarithmic fitting.
How do I fit y = A*exp(Bx) + C ? The result should be an np.array of [A, B, C]. I know that polyfit performs bad for this function, so I would like to use curve_fit to solve the problem, and it should start from initial guess p0.
A:
<code>
import numpy as np
import scipy.optimize
y = np.array([1, 7, 20, 50, 79])
x = np.array([10, 19, 30, 35, 51])
p0 = (4, 0.1, 1)
</code>
result = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Scipy

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Source and history

upstream_id / Original problem ID
713
task_id
3b65ff5c-d832-51bc-aa5e-d3bd1e148d2f
task_key
default--test--713
task_revision_id
1
config / split
default / test

Official source

initial import