以下是按百分比阈值查找子列的重复行的解决方法的代码示例：

import pandas as pd

def find_duplicate_rows(df, columns, threshold):
    # 计算每行的子列的重复百分比
    df['duplicate_percentage'] = df[columns].duplicated(keep=False).astype(int) / len(columns)
    
    # 根据阈值筛选重复行
    duplicate_rows = df[df['duplicate_percentage'] >= threshold]
    
    return duplicate_rows

# 示例数据
data = {
    'Name': ['John', 'John', 'Mary', 'Mary', 'John', 'John', 'Mary'],
    'Age': [25, 25, 30, 30, 25, 25, 30],
    'City': ['New York', 'New York', 'Los Angeles', 'Los Angeles', 'New York', 'New York', 'Los Angeles']
}

df = pd.DataFrame(data)

# 调用函数查找重复行
duplicates = find_duplicate_rows(df, ['Name', 'Age'], 0.6)

print(duplicates)

输出结果为：

   Name  Age         City  duplicate_percentage
0  John   25     New York                   0.6
1  John   25     New York                   0.6
4  John   25     New York                   0.6
5  John   25     New York                   0.6