Coin flip simulator to find how many flips are required to produce x consecutive "heads" flips.

coin_flip_sim.py

# Example of a coin flip simulator
# with a statistical summary

import random, pandas as pd

def flip():
    if random.uniform(0.0,1.0)  >= 0.5:
        return "heads"
    return "tails"

def x_heads(x):
    log = []
    consec_heads = 0
    flip_count = 0
    while consec_heads < x:
        outcome = flip()
        if outcome == "heads":
            consec_heads += 1
        else:
            consec_heads = 0
        log.append(outcome)
        flip_count += 1
    return flip_count

def trials(f, x, trials=1000):
    result_log = []
    for i in range(trials):
        result = f(x)
        result_log.append(result)
    series = pd.Series(result_log)
    print "median\t" + str(series.median())
    print series.describe()

trials(x_heads, 10, trials=1000)