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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
Right now, I have my data in a 2D numpy array `a`. If I was to use MinMaxScaler fit_transform on the array, it will normalize it column by column, whereas I wish to normalize the entire np array all together. Is there anyway to do that?
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Python Code:
import numpy as np
from sklearn.preprocessing import MinMaxScaler
a = np.array([[-1, 2], [-0.5, 6]])
scaler = MinMaxScaler()
a_one_column = a.reshape(-1, 1)
result_one_column = scaler.fit_transform(a_one_column)
result = result_one_column.reshape(a.shape)
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