[python]Bootstrap 실습

In [160]:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

In [209]:

pop=pd.Series(np.random.randint(low=0,high=100000, size=10000))
goal=Pop.mean()
print(goal)

49410.77

In [210]:

sample=pop.sample(n=200)

In [211]:

sample.mean()

Out[211]:

49402.605

In [212]:

sample.std()

Out[212]:

28805.574408680783

In [213]:

m=sample.mean()
sd=1.96*sample.std()/np.sqrt(200)

In [214]:

print(m-sd,',',m+sd)

45410.35606793104 , 53394.85393206897

In [215]:

boot_1d = []
for i in range(10000):
    boot_mean = sample.sample(frac = 0.2,replace = True).mean()
    boot_1d.append(boot_mean)
boot_1d = pd.DataFrame(boot_1d)
boot_1d.plot(kind='density')

Out[215]:

<matplotlib.axes._subplots.AxesSubplot at 0xf9d74a8>

In [216]:

boot_1d.mean()[0]

Out[216]:

49318.83029

In [217]:

d=1.96*boot_1d.std()[0]/np.sqrt(200)

In [218]:

print(boot_1d.mean()[0]-d,",",boot_1d.mean()[0]+d)

48684.96310343525 , 49952.69747656475

In [1]:

from IPython.core.display import display, HTML
display(HTML("<style>.container {width:90% !important;}</style>"))

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