If you need to normalize a list of numbers in Python, then you can do the following:

Option 1 – Using Native Python

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list = [6,1,0,2,7,3,8,1,5]
print('Original List:',list)
xmin = min(list) 
xmax=max(list)
for i, x in enumerate(list):
    list[i] = (x-xmin) / (xmax-xmin)
print('Normalized List:',list)

Option 2 – Using MinMaxScaler from sklearn

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import numpy as np
from sklearn import preprocessing
list = np.array([6,1,0,2,7,3,8,1,5]).reshape(-1,1)
print('Original List:',list)
scaler = preprocessing.MinMaxScaler()
normalizedlist=scaler.fit_transform(list)
print('Normalized List:',normalizedlist)

You can also specify the range of the MinMaxScaler().

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import numpy as np
from sklearn import preprocessing
list = np.array([6,1,0,2,7,3,8,1,5]).reshape(-1,1)
print('Original List:',list)
scaler = preprocessing.MinMaxScaler(feature_range=(0, 3))
normalizedlist=scaler.fit_transform(list)
print('Normalized List:',normalizedlist)