利用tkinter和python建立数据集k匿名化系统将所有数据泛化处理并在处理后输出精确值步骤

1. 导入必要的库

import pandas as pd
import tkinter as tk
from tkinter import filedialog

2. 创建GUI界面并选择数据集

root = tk.Tk()
root.withdraw()

file_path = filedialog.askopenfilename()

3. 加载数据集

df = pd.read_csv(file_path)

4. 获取所有属性名并选择要进行泛化处理的属性

column_names = df.columns
selected_columns = []

for column in column_names:
    selected = input(f"Do you want to anonymize {column}? (y/n)")
    if selected.lower() == 'y':
        selected_columns.append(column)

5. 对要进行泛化处理的属性进行处理

for column in selected_columns:
    column_data = df[column]
    column_type = column_data.dtype

    if column_type == 'int64' or column_type == 'float64':
        max_value = column_data.max()
        min_value = column_data.min()
        range_value = max_value - min_value

        for i in range(len(column_data)):
            column_data[i] = int((column_data[i] - min_value) / range_value * 10)

        df[column] = column_data

    elif column_type == 'object':
        unique_values = column_data.unique()

        for i in range(len(column_data)):
            column_data[i] = unique_values.index(column_data[i])

        df[column] = column_data

6. 输出处理后的数据集

df.to_csv('anonymized_data.csv', index=False)
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