Describe the bug

By setting the copy=False, ndarray data has not changed unexpectedly

Steps/Code to Reproduce

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn.preprocessing as pre

np.random.seed(10)
data = np.random.randint(1, 10, size=(5, 3))
print(data)
pre.minmax_scale(data, feature_range=(0, 1), axis=0, copy=False)
print(data)

Expected Results

A reasonable explanation about the copy parameter of minmax_scala funciton

Actual Results

There are no warings and errors, just the result is not wrong!

Versions

Python dependencies:
      sklearn: 1.3.0
          pip: 23.2.1
   setuptools: 65.5.0
        numpy: 1.25.2
        scipy: 1.11.2
       Cython: None
       pandas: 2.0.3
   matplotlib: 3.7.2
       joblib: 1.3.2
threadpoolctl: 3.2.0