標准化數據的公式: (數據值 - 平均數) / 標准差
1 import numpy as np 2 3 employment = np.array([ 4 55.70000076, 51.40000153, 50.5 , 75.69999695, 5 58.40000153, 40.09999847, 61.5 , 57.09999847, 6 60.90000153, 66.59999847, 60.40000153, 68.09999847, 7 66.90000153, 53.40000153, 48.59999847, 56.79999924, 8 71.59999847, 58.40000153, 70.40000153, 41.20000076 9 ]) 10 11 mean = employment.mean() #計算平均數 12 deviation = employment.std() #計算標准差 13 # 標准化數據的公式: (數據值 - 平均數) / 標准差 14 standardized_employment = (employment - mean) / deviation 15 print (standardized_employment)
結果:
1 [-0.31965231 -0.780123 -0.87650077 1.82207181 -0.03051941 -1.99019768 2 0.30144772 -0.16973184 0.23719615 0.84758731 0.18365304 1.00821665 3 0.87971351 -0.56595055 -1.07996476 -0.20185762 1.38301845 -0.03051941 4 1.2545153 -1.87240259]