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bootstrapping python

Innocent Iguana answered on December 16, 2023 Popularity 3/10 Helpfulness 2/10

answer bootstrapping python

bootstrapping python

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# All possible combination of dice rolls
from itertools import product
die1 = die2 = die3 = die4 = die5 = [1,2,3,4,5,6,7,8]
dice = pd.DataFrame(list(product(die1, die2, die3, die4, die5 )), columns=['die1', 'die2', 'die3', 'die4', 'die5'])

# Bootstrapping example 1 : Simulating dice roll
sample_means_1000 = []
# Simulate 1000 turns of 4 dice rolls
for i in range(1000): 
    sample_means_1000.append( np.random.choice(list(range(1,7)), size=4, replace=True).mean() )
# Visualize distribution
plt.hist(sample_means_1000, bins=20)

# Bootstrapping example 2 : Resampling from existing sample
import numpy as np
sample_means = []
for i in range(1000):
	sample_means.append(np.mean(df.sample(frac=1, replace=True)['col']))

Popularity 3/10 Helpfulness 2/10 Language python

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Contributed on Dec 16 2023

Innocent Iguana

0 Answers Avg Quality 2/10

bootstrapping python

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