๐ Box plot์ ๋ํด์ ์์๋ณด์
์ถ์ฒ : ์ ๋ก๋ฒ ์ด์ค ๋ฐ์ดํฐ ์ค์ฟจ
samples = [1, 7, 9 , 16, 36, 39, 45, 45, 46, 48, 51, 100, 101]
tmp_y = [1]*len(samples)
import matplotlib.pyplot as plt
plt.figure(figsize=(12, 4))
plt.scatter(samples, tmp_y)
plt.grid()
plt.show()
๐ Percentile, Median (numpy)
๐ปMedian
import numpy as np
np.median(samples)
>>>>
45.0
๐ปQ1
# Q1
np.percentile(samples, 25)
>>>
16.0
๐ปQ3
# Q3
np.percentile(samples, 75)
>>>>
48.0
๐ปIQR (Q3 - Q1)
# IQR
np.percentile(samples, 75) - np.percentile(samples, 25)
>>>
32.0
๐ Boxplot์ ํ์ฉํ์ฌ ๋ฐฑ๋ถ์์ ํ์ธํด๋ณด๊ธฐ
q1 = np.percentile(samples, 25)
q2 = np.median(samples)
q3 = np.percentile(samples, 75)
iqr = q3 - q1
upper_fence = q3 + iqr*1.5
lower_fence = q1 - iqr*1.5
plt.figure(figsize=(12, 4))
plt.scatter(samples,tmp_y)
plt.axvline(x=q1, color='black')
plt.axvline(x=q2, color='red')
plt.axvline(x=q3, color='black')
plt.axvline(x=upper_fence, color='black', ls='dashed')
plt.axvline(x=lower_fence, color='black', ls='dashed')
plt.show()
์ถ์ฒ : ์ ๋ก๋ฒ ์ด์ค ๋ฐ์ดํฐ ์ค์ฟจ