43. 数据结构之字典

# 注：该代码块包含未完成的填空代码，需要在平台上完成
# ⚠️ 平台原始代码 - 请原样输入至教学平台（注释除外），平台才会判定答案正确
#任务一
dict1 = {"汇率变量":"美元兑人民币","日期":"2024-08-30","中间价":"7.1124","涨跌幅":"-0.0025"}  
dict2 = {"汇率变量":"欧元兑人民币","日期":"2024-08-21","中间价":"7.9325","涨跌幅":"0.0038"}  # 定义字典dict2
dict3 = {"汇率变量":"港元兑人民币","日期":"2024-08-19","中间价":"0.9162","涨跌幅":"-0.0003"}  # 定义字典dict3
dict4 = {"汇率变量":"英镑兑人民币","日期":"2024-08-08","中间价":"9.0701","涨跌幅":"0.0011"}  # 定义字典dict4

print(dict1.keys()) #输出字典dict1的全部键码

print(dict2.values()) #输出字典dict2的全部数值

print(dict3.items())  #输出字典dict3的全部元素


#任务二
dict1 = {"汇率变量":"美元兑人民币","日期":"2024-08-30","中间价":"7.1124","涨跌幅":"-0.0025"}  
dict2 = {"汇率变量":"欧元兑人民币","日期":"2024-08-21","中间价":"7.9325","涨跌幅":"0.0038"}  # 定义字典dict2
dict4 = {"汇率变量":"英镑兑人民币","日期":"2024-08-08","中间价":"9.0701","涨跌幅":"0.0011"}  # 定义字典dict4
 
print(dict1["日期"])   #查询美元兑人民币汇率的具体日期
 
print(dict2["中间价"])  #查询欧元兑人民币汇率的中间价
 
print(dict4["涨跌幅"])   #查询英镑兑人民币的涨跌幅
 
#任务三
dict2 = {"汇率变量":"欧元兑人民币","日期":"2024-08-21","中间价":"7.9325","涨跌幅":"0.0038"}
 
dict2["日期"] = "2024-08-29"           #修改字典2新的日期

dict2["中间价"] = 7.9318               #修改字典2新的中间价

dict2["涨跌幅"] = -0.0037              #修改字典2新的涨跌幅

print(dict2)  # 输出变量dict2的值

#任务四
dict3 = {"汇率变量":"港元兑人民币","日期":"2024-08-19","中间价":"0.9162","涨跌幅":"-0.0003"}

#使用update函数在dict3中添加"前一日中间价":"0.9165","前一日涨跌幅":"0.0002"
dict3.update({"前一日中间价":"0.9165","前一日涨跌幅":"0.0002"})   
print(dict3)  # 输出任务四
 
dict4 = {"汇率变量":"英镑兑人民币","日期":"2024-08-08","中间价":"9.0701","涨跌幅":"0.0011"}  # 定义字典dict4
del dict4["涨跌幅"]           #删除dict4的涨跌幅
print(dict4)  # 输出变量dict4的值

# 花括号{}是字典的字面量语法
# 键值对格式: 键:值，使用冒号分隔
stock_codes = {
    '600': '上证A股',
    '900': '上证B股',
    '000': '深证A股',
    '200': '深证B股',
    '400': '三板市场股票'
}
print('股票代码分类:', stock_codes)

# 方式2: dict()构造函数 —— 先创建空字典再逐个添加
stock_codes_b = dict()
stock_codes_b['600'] = '上证A股'
stock_codes_b['900'] = '上证B股'
print('构造函数:', stock_codes_b)

# 方式3: dict.fromkeys()批量创建 —— 所有值相同时使用
codes = ['600', '900', '000']
stock_codes_c = dict.fromkeys(codes, '其他')
print('fromkeys:', stock_codes_c)

# 创建股票代码到名称的映射
stock_dict = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液',
    '600036.SH': '招商银行'
}

# 推荐使用 get()方法 —— 键不存在时返回默认值，不报错
print('查询600519.SH:', stock_dict.get('600519.SH', '未知'))

# 查询不存在的键 —— 安全返回默认值
print('查询999999.XX:', stock_dict.get('999999.XX', '未知'))
# 如果用 stock_dict['999999.XX'] 会报 KeyError！

stock_dict = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液',
    '600036.SH': '招商银行'
}

# 添加新键值对（键已存在则覆盖）
stock_dict['601318.SH'] = '中国平安'
print('添加后:', stock_dict)

# del 删除键值对（键不存在会报 KeyError）
del stock_dict['600036.SH']
print('删除后:', stock_dict)

stock_dict = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液',
    '601318.SH': '中国平安'
}

# keys() 返回所有键
print('键:', list(stock_dict.keys()))

# values() 返回所有值
print('值:', list(stock_dict.values()))

# items() 返回所有键值对
print('项:', list(stock_dict.items()))

# len() 返回键值对数量
print('项数:', len(stock_dict))

stock_dict = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液'
}

# pop()：键不存在时返回默认值，不会报错
removed = stock_dict.pop('999999.XX', None)
print('删除不存在的键:', removed)  # None

# pop()：键存在时删除并返回值
removed = stock_dict.pop('000858.SZ', None)
print('删除的值:', removed)  # 五粮液
print('剩余字典:', stock_dict)

stock_dict = {'600519.SH': '贵州茅台'}

# update()：批量添加/更新键值对
new_stocks = {
    '000001.SZ': '平安银行',
    '601318.SH': '中国平安'
}
stock_dict.update(new_stocks)
print('更新后:', stock_dict)
# 键已存在 → 更新值；键不存在 → 添加新键值对

prices = {'贵州茅台': 1850, '五粮液': 220, '招商银行': 45}

# 方式1: 遍历键
print('遍历键:')
for key in prices:
    print(f'  {key}')

# 方式2: 遍历键值对（推荐）
print('\n遍历键值对:')
for key, value in prices.items():
    print(f'  {key}: {value}元')

# 方式3: 遍历值
print('\n遍历值:')
for value in prices.values():
    print(f'  {value}元')

prices = {'贵州茅台': 1850, '五粮液': 220, '招商银行': 45}

# 语法: {键表达式: 值表达式 for item in iterable}

# 应用1: 反转键值对
inverted = {v: k for k, v in prices.items()}
print('反转字典:', inverted)

# 应用2: 过滤 —— 只保留价格 > 100 的股票
expensive = {k: v for k, v in prices.items() if v > 100}
print('高价股:', expensive)

# 应用3: 转换 —— 价格转为万元
prices_wan = {k: v / 10000 for k, v in prices.items()}
print('万元价格:', prices_wan)

# 股票代码到名称的映射（查找表）
code_to_name = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液',
    '600036.SH': '招商银行',
    '601318.SH': '中国平安',
    '000001.SZ': '平安银行'
}

# 批量查询
codes_to_query = ['600519.SH', '000858.SZ', '000001.SZ']
print('股票查询结果:')
for code in codes_to_query:
    name = code_to_name.get(code, '未知股票')
    print(f'  {code}: {name}')

code_to_name = {
    '600519.SH': '贵州茅台',
    '000858.SZ': '五粮液',
    '601318.SH': '中国平安',
    '000001.SZ': '平安银行'
}

# 使用字典推导式交换键和值
name_to_code = {v: k for k, v in code_to_name.items()}

print('平安银行代码:', name_to_code.get('平安银行'))
print('腾讯代码:', name_to_code.get('腾讯'))  # None

# 持仓价值（元）
holdings = {
    '贵州茅台': 185000,
    '五粮液': 44000,
    '招商银行': 22500
}

total = sum(holdings.values())

# 计算权重
weights = {stock: value / total for stock, value in holdings.items()}

print('持仓权重:')
for stock, weight in sorted(weights.items(), key=lambda x: -x[1]):
    print(f'  {stock}: {weight:.2%}')

stock_info = {
    '600519.SH': {
        'name': '贵州茅台',
        'price': 1850.00,
        'pe': 45.2,
        'market_cap': 2325000000000
    },
    '000858.SZ': {
        'name': '五粮液',
        'price': 220.50,
        'pe': 32.8,
        'market_cap': 856000000000
    }
}

# 访问嵌套信息
maotai = stock_info['600519.SH']
print(f'{maotai["name"]}: PE={maotai["pe"]}, 市值={maotai["market_cap"]/1e8:.0f}亿元')

from collections import defaultdict

# 使用 defaultdict 避免手动检查键是否存在
# 当访问不存在的键时，自动创建默认值
counter = defaultdict(int)  # 默认值为 0

# 统计股票出现次数
codes = ['600519.SH', '000858.SZ', '600519.SH', '600519.SH']
for code in codes:
    counter[code] += 1  # 即使 code 不存在也不会报错

print(dict(counter))