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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 3 by 3 numpy array. 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
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
np_array = load_data()
scaler = MinMaxScaler()
X_one_column = np_array.reshape([-1, 1])
result_one_column = scaler.fit_transform(X_one_column)
transformed = result_one_column.reshape(np_array.shape)
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