01 Count outcomes using tree diagram#

%%html
<iframe width="700" height="400" src="https://www.youtube.com/embed/Zxvc6iPKdec/" frameborder="0" allowfullscreen></iframe>

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

khanacademy

Count outcomes using tree diagram fig 1Count outcomes using tree diagram fig 2

engines = ['4', '6']
colors = ['Red', 'Blue', 'Green', 'White']

tree = [i for i in itertools.product(engines, colors)]

tree

[('4', 'Red'),
 ('4', 'Blue'),
 ('4', 'Green'),
 ('4', 'White'),
 ('6', 'Red'),
 ('6', 'Blue'),
 ('6', 'Green'),
 ('6', 'White')]

G=nx.Graph()

for engine, color in tree:
    G.add_edge(engine, color)
    
nx.draw_networkx(G)
plt.show()
../_images/01 Count outcomes using tree diagram_8_0.png 
# find a better way to plot tree diagram