Binomial Distribution chart

#For a binomial distribution  you can input the number of experiments , trials and the probability of success
#Binomial_chart_matplotlib coded by Ken Adams
#The probability of success p_prob. the number of experiments and the number of trials are set.
#The code is run and a bar chart is displayed using matplotlib

import matplotlib.pyplot as plot
import random
print("This program makes a graph of a binonial distribution for a given probability of success 'p'")
print("Each experiment consists of a set number of trials and the total number of successes that occoured are recorded")
print("After running a set number of experiments a graph is plotted\n")

#These are the default values
experiments = 1000000
trials = 4
p_prob = 0.2
#random.seed(30)# for testing

print("The program will run on default values")
print(str(experiments) + " experiments, with " + str(trials) + " trials " + " and a probability of success of " +str(p_prob))




decision = input("do you want to change the parameters 'Y' or 'N' ? ")
if decision.lower()  == "y":
    experiments = int(input("How many experiments to run " ))
    trials = int(input("How many trials of each experiment? "))
    p_prob = float(input(" What probability for success do you want? enter a number betwen 0 ans 1 "))
else:
    print("OK we run on default paramenter")


results = [ ]
for y in range (experiments):
    p_count = 0
    for x in range(trials):

        raw = random.randint(0, 1000)
        #print(str(raw))
        if raw < 1000*p_prob:
            p_count = p_count +1
    results.append(p_count)
# for testing ##print("results") #print(results) #print("p_count is: " + str(p_count))


def score_freq(scores_list):
    freq = []
    for x in range(trials+1):
        score_x = scores_list.count(x)
        freq.append(score_x)
    return freq

performance = score_freq(results)
print("performance")
print(performance)


# The rest of the code is for plotting
plot.bar(range(trials+1), performance, align='center', alpha=0.5)

plot.xticks(range(trials+1))
plot.ylabel('Number of successes')
plot.title("Binomial distribution over " +str(experiments) + " experiments of " + str(trials) + " trials with p = " + str(p_prob))

plot.show()
#plot.savefig(fname="2.10(102) binomial.png") # can save if you wish

print("bye")