Python中四大核心数据结构(列表,元组,字典和集合)的完全解析

# 创建-操作-输出完整演示
# 初始化商品列表
products = ["手机", "笔记本", "耳机", "鼠标"]

print("原始列表:", products)  # ['手机', '笔记本', '耳机', '鼠标']

# 索引访问与切片
print("首个商品:", products[0])      # 手机
print("最后两个商品:", products[-2:]) # ['耳机', '鼠标']

# 元素修改与扩展
products[1] = "游戏本"             # 修改元素
products.append("键盘")           # 追加元素
products.insert(2, "显示器")      # 插入元素

print("修改后列表:", products)    # ['手机', '游戏本', '显示器', '耳机', '鼠标', '键盘']

# 删除操作
removed_item = products.pop(3)    # 删除索引3的元素
print("被删除商品:", removed_item) # 耳机
print("当前列表:", products)      # ['手机', '游戏本', '显示器', '鼠标', '键盘']

# 创建数字列表
nums = [3, 1, 4, 1, 5, 9]

# 排序与反转
nums.sort()                     # 升序排列 [1, 1, 3, 4, 5, 9]
nums.reverse()                  # 反转列表 [9, 5, 4, 3, 1, 1]

# 列表推导式
squares = [x**2 for x in nums if x > 3]
print("大数平方:", squares)     # [81, 25, 16]

# 其他实用方法
print("出现次数:", nums.count(1))  # 2
nums.clear()                    # 清空列表

# 定义-访问-解包全流程
# 创建坐标元组
point = (10, 20)

# 索引访问
print("X坐标:", point[0])    # 10
print("Y坐标:", point[1])    # 20

# 元组解包
x, y = point
print(f"坐标位置: ({x}, {y})")  # (10, 20)

# 类型转换示例
list_point = list(point)      # 转为列表可修改
list_point[0] += 5
new_point = tuple(list_point)
print("新坐标:", new_point)   # (15, 20)

# 函数返回多个值
def get_dimensions():
    return 1920, 1080

width, height = get_dimensions()
print(f"分辨率: {width}x{height}")

# 创建-更新-遍历完整示例
# 初始化学生信息
student = {
    "name": "张三",
    "age": 18,
    "courses": ["数学", "英语"]
}

# 添加新信息
student["gender"] = "男"
student["age"] = 19          # 修改年龄

# 安全获取值
score = student.get("score", 0)
print("默认分数:", score)    # 0

# 删除元素
removed = student.pop("courses")
print("已删除课程:", removed) # ['数学', '英语']

# 遍历字典
print("\n学生详细信息:")
for key, value in student.items():
    print(f"{key}: {value}")

"""
输出:
学生详细信息:
name: 张三
age: 19
gender: 男
"""

# 字典合并与推导式
grades = {"数学": 90, "英语": 85}
extra_grades = {"编程": 95, "物理": 88}

# 合并字典
grades.update(extra_grades)

# 字典推导式
passed = {subject: score for subject, score in grades.items() if score >= 85}
print("及格科目:", passed)  # {'数学':90, '英语':85, '编程':95, '物理':88}

# 键值反转
inverted_dict = {v: k for k, v in grades.items()}
print("分数对照:", inverted_dict)  # {90: '数学', 85: '英语', ...}

# 创建-运算-方法全流程
# 初始化集合
A = {1, 2, 3, 4}
B = {3, 4, 5, 6}

print("原始集合A:", A)  # {1,2,3,4}
print("原始集合B:", B)  # {3,4,5,6}

# 集合运算
print("并集:", A | B)   # {1,2,3,4,5,6}
print("差集:", A - B)   # {1,2}
print("对称差集:", A ^ B) # {1,2,5,6}

# 元素操作
A.add(5)                # 添加元素
A.discard(2)            # 安全删除
print("更新后A:", A)    # {1,3,4,5}

# 集合推导式
even_numbers = {x for x in range(10) if x%2 == 0}
print("偶数集合:", even_numbers)  # {0,2,4,6,8}

def data_cleaner(raw_data):
    # 列表存储有效数据
    cleaned = []
    
    # 集合记录已处理项
    seen = set()
    
    # 字典统计频率
    counter = {}
    
    for item in raw_data:
        # 去重处理
        if item not in seen:
            cleaned.append(item)
            seen.add(item)
        
        # 统计频率
        counter[item] = counter.get(item, 0) + 1
    
    # 元组保存元信息
    meta = (len(raw_data), len(cleaned))
    
    return {
        "cleaned_data": cleaned,
        "frequency": counter,
        "metadata": meta
    }

# 测试数据
test_data = ["A", "B", "A", "C", "B", "D"]
result = data_cleaner(test_data)
print(result)
"""
输出:
{
    'cleaned_data': ['A', 'B', 'C', 'D'],
    'frequency': {'A':2, 'B':2, 'C':1, 'D':1},
    'metadata': (6, 4)
}
"""