Can someone help me code this using python?

The motion of a kinesin motor protein on a microtubule can be thought of as a one-dimensional random walk, where at each step of unit length, the protein either goes forward with probability p or reverse with probability 1 - p. Write a function that accepts values of p and number of steps N and returns the position x of a random walker after N steps, starting at the origin. Write a driver routine that calls this function 1000 times and stores the end positions in an array. Plot the distribution of end points in the form of a normalized histogram for N = 200 and p = 0.5, 0.6, 0.7. What do you observe? For a large number of steps, the distribution of end points should be described by a Gaussian distribution P(x) = exp [(x - x_0)^2/2 sigma^2]/squareroot 2 pi sigma^2. Fit P(x) to the three distributions you computed in (c), report the fit values for x_0 and sigma, and compare to the expected values from theory