如何迭代pandas数据帧中所有输入变量的秩归一化

import pandas as pd
from sklearn.preprocessing import MinMaxScaler

df = pd.read_csv('data.csv')

df_normalized = pd.DataFrame()

for column in df.columns:
    # 获取当前列的数据
    data = df[column].values.reshape(-1, 1)
    
    # 创建MinMaxScaler对象
    scaler = MinMaxScaler()
    
    # 对当前列进行秩归一化
    normalized_data = scaler.fit_transform(data)
    
    # 将归一化后的数据添加到新的DataFrame中
    df_normalized[column] = normalized_data.flatten()

print(df_normalized)