파이썬 기초 퀴즈_5

문제 1

"iris.csv" 를 읽어오면 (150,5) 의 Numpy 어레이로 만들 수 있다. 5개의 속성을 정규화 하라. 즉, 각 속성은 평균은 0, 표준편차가 1이 되어야 한다.

문제 2

아래의 코드에서 마지막 칼럼의 값이 0 보다 큰 샘플을 모두 구하라.

import numpy as np

a = np.random.randn(10,3)

정답

1번¶

In [8]:

f=open('iris.csv')

line=f.readline()
feature=line.strip().split(',')

labels = ['Iris-setosa', 'Iris-versicolor', 'Iris-virginica']

data=[]
for line in f:
    l = line.strip().split(',')
    
    l[:4]=[float(i) for i in l[:4]]
    
    l[4] = labels.index(l[4])
    
    data.append(l)
    
f.close()

iris = np.array(data)

In [9]:

iris_norm = (iris - iris.mean(axis=0))/iris.std(axis=0)
iris_norm.shape

Out[9]:

(150, 5)

In [10]:

iris_norm

Out[10]:

array([[-9.00681170e-01,  1.03205722e+00, -1.34127240e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.14301691e+00, -1.24957601e-01, -1.34127240e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.38535265e+00,  3.37848329e-01, -1.39813811e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.50652052e+00,  1.06445364e-01, -1.28440670e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.02184904e+00,  1.26346019e+00, -1.34127240e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-5.37177559e-01,  1.95766909e+00, -1.17067529e+00,
        -1.05003079e+00, -1.22474487e+00],
       [-1.50652052e+00,  8.00654259e-01, -1.34127240e+00,
        -1.18150376e+00, -1.22474487e+00],
       [-1.02184904e+00,  8.00654259e-01, -1.28440670e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.74885626e+00, -3.56360566e-01, -1.34127240e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.14301691e+00,  1.06445364e-01, -1.28440670e+00,
        -1.44444970e+00, -1.22474487e+00],
       [-5.37177559e-01,  1.49486315e+00, -1.28440670e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.26418478e+00,  8.00654259e-01, -1.22754100e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.26418478e+00, -1.24957601e-01, -1.34127240e+00,
        -1.44444970e+00, -1.22474487e+00],
       [-1.87002413e+00, -1.24957601e-01, -1.51186952e+00,
        -1.44444970e+00, -1.22474487e+00],
       [-5.25060772e-02,  2.18907205e+00, -1.45500381e+00,
        -1.31297673e+00, -1.22474487e+00],
       [-1.73673948e-01,  3.11468391e+00, -1.28440670e+00,
        -1.05003079e+00, -1.22474487e+00],
       [-5.37177559e-01,  1.95766909e+00, -1.39813811e+00,
        -1.05003079e+00, -1.22474487e+00],
       [-9.00681170e-01,  1.03205722e+00, -1.34127240e+00,
        -1.18150376e+00, -1.22474487e+00],
       [-1.73673948e-01,  1.72626612e+00, -1.17067529e+00,
        -1.18150376e+00, -1.22474487e+00],
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       [ 6.74501145e-01,  3.37848329e-01,  4.21564419e-01,
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       [ 2.24968346e+00, -1.24957601e-01,  1.33141568e+00,
         1.44795564e+00,  1.22474487e+00],
       [ 5.53333275e-01,  8.00654259e-01,  1.04708716e+00,
         1.57942861e+00,  1.22474487e+00],
       [ 6.74501145e-01,  1.06445364e-01,  9.90221459e-01,
         7.90590793e-01,  1.22474487e+00],
       [ 1.89829664e-01, -1.24957601e-01,  5.92161531e-01,
         7.90590793e-01,  1.22474487e+00],
       [ 1.28034050e+00,  1.06445364e-01,  9.33355755e-01,
         1.18500970e+00,  1.22474487e+00],
       [ 1.03800476e+00,  1.06445364e-01,  1.04708716e+00,
         1.57942861e+00,  1.22474487e+00],
       [ 1.28034050e+00,  1.06445364e-01,  7.62758643e-01,
         1.44795564e+00,  1.22474487e+00],
       [-5.25060772e-02, -8.19166497e-01,  7.62758643e-01,
         9.22063763e-01,  1.22474487e+00],
       [ 1.15917263e+00,  3.37848329e-01,  1.21768427e+00,
         1.44795564e+00,  1.22474487e+00],
       [ 1.03800476e+00,  5.69251294e-01,  1.10395287e+00,
         1.71090158e+00,  1.22474487e+00],
       [ 1.03800476e+00, -1.24957601e-01,  8.19624347e-01,
         1.44795564e+00,  1.22474487e+00],
       [ 5.53333275e-01, -1.28197243e+00,  7.05892939e-01,
         9.22063763e-01,  1.22474487e+00],
       [ 7.95669016e-01, -1.24957601e-01,  8.19624347e-01,
         1.05353673e+00,  1.22474487e+00],
       [ 4.32165405e-01,  8.00654259e-01,  9.33355755e-01,
         1.44795564e+00,  1.22474487e+00],
       [ 6.86617933e-02, -1.24957601e-01,  7.62758643e-01,
         7.90590793e-01,  1.22474487e+00]])

2번¶

In [11]:

import numpy as np
a = np.random.randn(10,3)
a[:,2][a[:,2]>0]

Out[11]:

array([3.38086697, 0.52316581, 0.13016702, 0.00418089, 2.90785333])