Coin Experiment.py

import numpy as np
import matplotlib.pyplot as plt

def coinFlip(p):
    #perform the binomial distribution (returns 0 or 1)
    result = np.random.binomial(1,p)
#return flip to be added to numpy array
    return result
'''Main Area'''
#probability of heads vs. tails. This can be changed.
probability = .5
#num of flips required. This can be changed.
n = 500
#initiate array
fullResults = np.arange(n)
#perform desired numbered of flips at required probability set above
for i in range(0, n):
    fullResults[i] = coinFlip(probability)
    i+=1
#print results
print("probability is set to ", probability)
print("Tails = 0, Heads = 1: ", fullResults)
#Total up heads and tails for easy user experience
print("Head Count: ", np.count_nonzero(fullResults == 1))
print("Tail Count: ", np.count_nonzero(fullResults == 0))
def coinFlip(size):
    flips = np.random.randint(0, 2, size=size)
    return flips.mean()
coinFlip = np.frompyfunc(coinFlip, 1, 1)

xmin, xmax, dx = 1, 500, 1
x = np.arange(xmin, xmax, dx)
y = coinFlip(x)
plt.plot(x, y)
plt.show()