Graphical presentation of stock prices at options' maturity dates

Up to now, we have discussed that options are really path-independent, which means the option prices depend on terminal values. Thus, before pricing such an option, we need to know the terminal stock prices. To extend the previous program, we have the following code to estimate the terminal stock prices for a given set of values: S0 (initial stock price), n_simulation (number of terminal prices), T (maturity date in years), n_steps (number of steps), mu (expected annual stock returns), and sigma (volatility):

import scipy as sp 
import matplotlib.pyplot as plt
from scipy import zeros, sqrt, shape 
#input area
S0 = 9.15               # stock price at time zero 
T =1.                   # years
n_steps=100.            # number of steps 
mu =0.15                # expected annual return 
sigma = 0.2             # volatility (annual) 
sp.random.seed(12345)   # fix those random numbers 
n_simulation = 1000     # number of simulation...