import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
pd.set_option('display.mpl_style', 'default')

# A function to flip a coin `num_times` times.
def flip_coin(num_times):
    coin_flips = np.random.randint(0, 2, num_times)
    counts = pd.Series(coin_flips).value_counts().reindex([0,1]).fillna(0)
    counts.index = ['heads', 'tails']
    return counts

flip_coin(10)

flip_coin(20)

flip_coin(10000)

def mustard_likers_null_hypothesis(sample_size): 
    coin_flips = flip_coin(sample_size)
    return coin_flips.ix['heads']
counts = pd.Series([mustard_likers_null_hypothesis(10) for i in range(10000)]).value_counts().sort_index()
counts

counts.plot(kind='bar')

mustard_likers = pd.Series([mustard_likers_null_hypothesis(10000) for i in range(10000)]).value_counts().sort_index()

plt.xlabel("Number of people who say they like mustard")
plt.ylabel("Frequency")
mustard_likers.reindex(np.arange(0, 10001)).fillna(0).plot()

plt.xlabel("Number of people who say they like mustard")
plt.ylabel("Frequency")
mustard_likers.reindex(np.arange(4700, 5301)).plot()