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import pandas as pd
import numpy as np
from sklearn.preprocessing import MinMaxScaler,Normalizer,StandardScaler
data = pd.DataFrame(
    {
        'a':[1,2,3],
        'b':[5,6,6],
        'c':[9,100,2]
    }
)
#归一化(MinMaxScaler)
min_max_scaler = MinMaxScaler()
min_max_scaler_data=min_max_scaler.fit_transform(data)
print(min_max_scaler_data)

#标准化(StandardScaler)
scale_x = StandardScaler()
scale_data = scale_x.fit_transform(data)
print(scale_data)

#正则化(Normalizer)
normalizer = Normalizer()
normalizer_data = normalizer.fit_transform(data)
print(normalizer_data)

运行结果：

[[0.         0.         0.07142857]
 [0.5        1.         1.        ]
 [1.         1.         0.        ]]
[[-1.22474487 -1.41421356 -0.62725005]
 [ 0.          0.70710678  1.41131261]
 [ 1.22474487  0.70710678 -0.78406256]]
[[0.09667365 0.48336824 0.87006284]
 [0.01996012 0.05988036 0.99800598]
 [0.42857143 0.85714286 0.28571429]]