12 Dependent probability introduction

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import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import matplotlib.pyplot as plt
import seaborn as sns

khanacademy

bag = set(['Green1', 'Green2', 'Green3', 'Orange1', 'Orange2'])

def P(cond, total_lst):
    cond_lst = list(filter(cond, total_lst))
    return len(cond_lst) / len(total_lst), cond_lst

p_green_st, _ = P(lambda x: x.startswith('Green'), bag)
print(p_green_st)

0.6

bag -= set(['Green1'])
p_green_nd, _ = P(lambda x: x.startswith('Green'), bag)
print(p_green_nd)

0.5

#P(1st Green AND 2nd Green) = P(1st Green) . P(2nd Green | 1st Green)
p_green_st * p_green_nd

0.3